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At least 307 records · Page 17

Membrane lipid and expression responses of Saccharolobus islandicus REY15A to acid and cold stress

Archaea adjust the number of cyclopentane rings in their glycerol dibiphytanyl glycerol tetraether (GDGT) membrane lipids as a homeostatic response to environmental stressors such as temperature, pH, and energy availability shifts. However, archaeal expression patterns that correspond with changes in GDGT composition are less understood. Here we characterize the acid and cold stress responses of the thermoacidophilic crenarchaeon Saccharolobus islandicus REY15A using growth rates, core GDGT lipid profiles, transcriptomics and proteomics. We show that both stressors result in impaired growth, lower average GDGT cyclization, and differences in gene and protein expression. Transcription data revealed differential expression of the GDGT ring synthase grsB in response to both acid stress and cold stress. Although the GDGT ring synthase encoded by grsB forms highly cyclized GDGTs with ≥5 ring moieties, S. islandicus grsB upregulation under acidic pH conditions did not correspond with increased abundances of highly cyclized GDGTs. Our observations highlight the inability to predict GDGT changes from transcription data alone. Broader analysis of transcriptomic data revealed that S. islandicus differentially expresses many of the same transcripts in response to both acid and cold stress. These included upregulation of several biosynthetic pathways and downregulation of oxidative phosphorylation and motility. Transcript responses specific to either of the two stressors tested here included upregulation of genes related to proton pumping and molecular turnover in acid stress conditions and upregulation of transposases in cold stress conditions. Overall, our study provides a comprehensive understanding of the GDGT modifications and differential expression characteristic of the acid stress and cold stress responses in S. islandicus.

59 BASIC BIOLOGICAL SCIENCES↗

Transcriptome sequencing and differential gene expression analysis in Viola yedoensis Makino (Fam. Violaceae) responsive to cadmium (Cd) pollution

Viola yedoensis Makino is an important Chinese traditional medicine plant adapted to cadmium (Cd) pollution regions. Illumina sequencing technology was used to sequence the transcriptome of V. yedoensis Makino. We sequenced Cd-treated (VIYCd) and untreated (VIYCK) samples of V. yedoensis, and obtained 100,410,834 and 83,587,676 high quality reads, respectively. After de novo assembly and quantitative assessment, 109,800 unigenes were finally generated with an average length of 661 bp. We then obtained functional annotations by aligning unigenes with public protein databases including NR, NT, SwissProt, KEGG and COG. In addition, 892 differentially expressed genes (DEGs) were investigated between the two libraries of untreated (VIYCK) and Cd-treated (VIYCd) plants. Moreover, 15 randomly selected DEGs were further validated with qRT-PCR and the results were highly accordant with the Solexa analysis. This study firstly generated a successful global analysis of the V. yedoensis transcriptome and it will provide for further studies on gene expression, genomics, and functional genomics in Violaceae. - Highlights: • A de novo assembly generated 109,800 unigenes and 5,4479 of them were annotated. • 31,285 could be classified into 26 COG categories. • 263 biosynthesis pathways were predicted and classified into five categories. • 892 DEGs were detected and 15 of them were validated by qRT-PCR.

60 APPLIED LIFE SCIENCES↗

Signature analysis of high-throughput transcriptomics screening data for mechanistic inference and chemical grouping

Abstract High-throughput transcriptomics (HTTr) uses gene expression profiling to characterize the biological activity of chemicals in in vitro cell-based test systems. As an extension of a previous study testing 44 chemicals, HTTr was used to screen an additional 1,751 unique chemicals from the EPA’s ToxCast collection in MCF7 cells using 8 concentrations and an exposure duration of 6 h. We hypothesized that concentration-response modeling of signature scores could be used to identify putative molecular targets and cluster chemicals with similar bioactivity. Clustering and enrichment analyses were conducted based on signature catalog annotations and ToxPrint chemotypes to facilitate molecular target prediction and grouping of chemicals with similar bioactivity profiles. Enrichment analysis based on signature catalog annotation identified known mechanisms of action (MeOAs) associated with well-studied chemicals and generated putative MeOAs for other active chemicals. Chemicals with predicted MeOAs included those targeting estrogen receptor (ER), glucocorticoid receptor (GR), retinoic acid receptor (RAR), the NRF2/KEAP/ARE pathway, AP-1 activation, and others. Using reference chemicals for ER modulation, the study demonstrated that HTTr in MCF7 cells was able to stratify chemicals in terms of agonist potency, distinguish ER agonists from antagonists, and cluster chemicals with similar activities as predicted by the ToxCast ER Pathway model. Uniform manifold approximation and projection (UMAP) embedding of signature-level results identified novel ER modulators with no ToxCast ER Pathway model predictions. Finally, UMAP combined with ToxPrint chemotype enrichment was used to explore the biological activity of structurally related chemicals. The study demonstrates that HTTr can be used to inform chemical risk assessment by determining in vitro points of departure, predicting chemicals’ MeOA and grouping chemicals with similar bioactivity profiles.

Toxicology↗

Bayesian Framework for Predicting and Controlling Metabolic Phenotypes in Microbial System

To improve titers, rates and yields for sucrose production in an engineered strain of Synechococcus elongatus PCC7942, we employed Bayesian metabolic control analysis to transcriptomics and external metabolomics data generated for various phases during the circadian clock. Top overexpression candidates included sodium-dependent bicarbonate transporter (H2cO3_Nat_syn), and UTP—glucose-1-phosphate uridylyltransferase (GALUi). Top repression candidates included Glycogen/starch synthetases, ADP-glucose type (GLCS3), Glutamate racemase (GLUR), and ribonucleoside diphosphate reductase (RNDR1).

60 APPLIED LIFE SCIENCES↗

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440

ABSTRACT There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules (“functional modules”), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida . Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

09 BIOMASS FUELS↗

Inorganic nitrogen availability alters Eucalyptus grandis receptivity to the ectomycorrhizal fungus Pisolithus albus but not symbiotic nitrogen transfer

Forest trees are able to thrive in nutrient-poor soils in part because they obtain growth-limiting nutrients, especially nitrogen (N), through mutualistic symbiosis with ectomycorrhizal (ECM) fungi. Addition of inorganic N into these soils is known to disrupt this mutualism and reduce the diversity of ECM fungi. Despite its ecological impact, the mechanisms governing the observed effects of elevated inorganic N on mycorrhizal communities remain unknown. Here, we address this by using a compartmentalized in vitro system to independently alter nutrients to each symbiont. Using stable isotopes, we traced the nutrient flux under different nutrient regimes between Eucalyptus grandis and its ectomycorrhizal symbiont, Pisolithus albus. We demonstrate that giving E. grandis independent access to N causes a significant reduction in root colonization by P. albus. Transcriptional analysis suggests that the observed reduction in colonization may be caused, in part, by altered transcription of microbe perception genes and defence genes. We show that delivery of N to host leaves is not increased by host nutrient deficiency but by fungal nutrient availability instead. Overall, this advances our understanding of the effects of N fertilization on ECM fungi and the factors governing nutrient transfer in the E. grandis-P. microcarpus interaction.

59 BASIC BIOLOGICAL SCIENCES↗

Bioenergy sorghum nodal root bud development: morphometric, transcriptomic and gene regulatory network analysis

Bioenergy sorghum’s large and deep nodal root system and associated microbiome enables uptake of water and nutrients from and deposition of soil organic carbon into soil profiles, key contributors to the crop’s resilience and sustainability. The goal of this study was to increase our understanding of bioenergy sorghum nodal root bud development. Sorghum nodal root bud initiation was first observed on the stem node of the 7 th phytomer below the shoot apex. Buds were initiated near the upper end of the stem node pulvinus on the side of the stem opposite the tiller bud, then additional buds were added over the next 6-8 days forming a ring of 10-15 nascent nodal root buds around the stem. Later in plant development, a second ring of nodal root buds began forming on the 17 th stem node immediately above the first ring of buds. Overall, nodal root bud development can take ~40 days from initiation to onset of nodal root outgrowth. Nodal root buds were initiated in close association with vascular bundles in the rind of the pulvinus. Stem tissue forming nascent nodal root buds expressed sorghum homologs of genes associated with root initiation (WOX4), auxin transport (LAX2, PIN4), meristem activation (NGAL2), and genes involved in cell proliferation. Expression of WOX11 and WOX5, genes involved in root stem niche formation, increased early in nodal root bud development followed by genes encoding PLTs, LBDs (LBD29), LRP1, SMB, RGF1 and root cap LEAs later in development. A nodal root bud gene regulatory network module expressed during nodal root bud initiation predicted connections linking PFA5, SPL9 and WOX4 to genes involved in hormone signaling, meristem activation, and cell proliferation. A network module expressed later in development predicted connections among SOMBRERO, a gene involved in root cap formation, and GATA19, BBM, LBD29 and RITF1/RGF1 signaling. Overall, this study provides a detailed description of bioenergy sorghum nodal root bud development and transcriptome information useful for understanding the regulation of sorghum nodal root bud formation and development.

09 BIOMASS FUELS↗

Developmental dynamics of stem starch accumulation in Sorghum bicolor

Sweet sorghums were identified that accumulate up to ~9% of their total stem dry weight as starch. Starch accumulated preferentially in stem pith parenchyma in close proximity to vascular bundles. Stem starch accumulated slowly between floral initiation and anthesis and more rapidly between anthesis and 43 days post-anthesis before declining in parallel with tiller outgrowth. Genes involved in stem starch metabolism were identified through phylogenetic approaches and RNA-seq analysis of Della stem gene expression during the starch accumulation phase of development. Genes differentially expressed in stems were identified that are involved in starch biosynthesis (i.e., AGPase SS/LS, starch synthases, starch-branching enzymes), degradation (i.e., glucan-water dikinase, β-amylase, disproportionating enzyme, alpha-glucan phosphorylase) and amyloplast sugar transport (glucose-6-P translocator). Transcripts encoding AGPase SS and LS subunits with plastid localization were differentially induced during stem starch accumulation indicating that ADP-glucose for starch biosynthesis is primarily generated in stem plastids. Cytosolic heteroglucan metabolism may play a role in stem sucrose/starch accumulation because genes encoding cytosolic forms of the disproportionating enzyme and alpha-glucan phosphorylase were induced in parallel with stem sucrose/starch accumulation. Information on the stem starch pathway obtained in this study will be useful for engineering sorghum stems with elevated starch thereby improving forage quality and the efficiency of biomass conversion to biofuels and bio-products.

59 BASIC BIOLOGICAL SCIENCES↗

Global Analysis of Chlorella variabilis NC64A mRNA Profiles during the Early Phase of Paramecium bursaria Chlorella Virus-1 Infection

The PBCV-1/Chlorella variabilis NC64A system is a model for studies on interactions between viruses and algae. Here we present the first global analyses of algal host transcripts during the early stages of infection, prior to virus replication. During the course of the experiment stretching over 1 hour, about a third of the host genes displayed significant changes in normalized mRNA abundance that either increased or decreased compared to uninfected levels. The population of genes with significant transcriptional changes gradually increased until stabilizing at 40 minutes post infection. Functional categories including cytoplasmic ribosomal proteins, jasmonic acid biosynthesis and anaphase promoting complex/cyclosomes had a significant excess in upregulated genes, whereas spliceosomal snRNP complexes and the shikimate pathway had significantly more down-regulated genes, suggesting that these pathways were activated or shut-down in response to the virus infection. Lastly, we examined the expression of C. varibilis RNA polymerase subunits, as PBCV-1 transcription depends on host RNA polymerases. Two subunits were up-regulated, RPB10 and RPC34, suggesting that they may function to support virus transcription. These results highlight genes and pathways, as well as overall trends, for further refinement of our understanding of the changes that take place during the early stages of viral infection.

59 BASIC BIOLOGICAL SCIENCES↗

Identification and selection of optimal reference genes for qPCR-based gene expression analysis in Fucus distichus under various abiotic stresses

Quantitative gene expression analysis is an important tool in the scientist’s belt. The identification of evenly expressed reference genes is necessary for accurate quantitative gene expression analysis, whether by traditional RT-PCR (reverse-transcription polymerase chain reaction) or by qRT-PCR (quantitative real-time PCR; qPCR). In the Stramenopiles (the major line of eukaryotes that includes brown algae) there is a noted lack of known reference genes for such studies, largely due to the absence of available molecular tools. Here we present a set of nine reference genes (Elongation Factor 1 alpha (EF1A), Elongation Factor 2 alpha (EF2A), Elongation Factor 1 beta (EF1B), 14-3-3 Protein, Ubiquitin Conjugating Enzyme (UBCE2), Glyceraldehyde-3-phosphate Dehydrogenase (GAPDH), Actin Related Protein Complex (ARP2/3), Ribosomal Protein (40s; S23), and Actin) for the brown alga Fucus distichus . These reference genes were tested on adult sporophytes across six abiotic stress conditions (desiccation, light and temperature modification, hormone addition, pollutant exposure, nutrient addition, and wounding). Suitability of these genes as reference genes was quantitatively evaluated across conditions using standard methods and the majority of the tested genes were evaluated favorably. However, we show that normalization genes should be chosen on a condition-by-condition basis. We provide a recommendation that at least two reference genes be used per experiment, a list of recommended pairs for the conditions tested here, and a procedure for identifying a suitable set for an experimenter’s unique design. With the recent expansion of interest in brown algal biology and accompanied molecular tools development, the variety of experimental conditions tested here makes this study a valuable resource for future work in basic biology and understanding stress responses in the brown algal lineage.

59 BASIC BIOLOGICAL SCIENCES↗

Transcriptome Profiling of Rust Resistance in Switchgrass Using RNA-Seq Analysis

Switchgrass rust caused by Puccinia emaculata is a major limiting factor for switchgrass (Panicum virgatum L.) production, especially in monoculture. Natural populations of switchgrass displayed diverse reactions to P. emaculata when evaluated in an Ardmore, OK, field. In order to identify the differentially expressed genes during the rust infection process and the mechanisms of switchgrass rust resistance, transcriptome analysis using RNA-Seq was conducted in two pseudo-F 1 parents ('PV281' and 'NFGA472'), and three moderately resistant and three susceptible progenies selected from a three-generation, four-founder switchgrass population (K5 x A4) x (AP13 x VS16). On average, 23.5 million reads per sample (leaf tissue was collected at 0, 24, and 60 h post-inoculation (hpi)) were obtained from paired-end (2 x 100 bp) sequencing on the Illumina HiSeq2000 platform. Furthermore, mapping of the RNA-Seq reads to the switchgrass reference genome (AP13 ver. 1.1 assembly) constructed a total of 84,209 transcripts from 98,007 gene loci among all of the samples. Further analysis revealed that host defense- related genes, including the nucleotide binding site-leucinerich repeat domain containing disease resistance gene analogs, play an important role in resistance to rust infection. Rust-induced gene (RIG) transcripts inherited across generations were identified. The rust-resistant gene transcripts can be a valuable resource for developing molecular markers for rust resistance. Finally we identified the rust-resistant genotypes and gene transcripts which can expedite rust-resistant cultivar development in switchgrass.

59 BASIC BIOLOGICAL SCIENCES↗

Hydrogen Regulation and Global Responses to Electron, Carbon and Nitrogen Sources of Methanococcus Maripaludis

Methanogens catalyze the critical, methane-producing step (called methanogenesis) in the anaerobic decomposition of organic matter. This project has generated the first predictive model of global gene regulation of methanogenesis in a hydrogenotrophic methanogen, Methanococcus maripaludis. We generated a comprehensive list of genes (protein-coding and non-coding) for M. maripaludis through integrated analysis of the transcriptome structure and a newly constructed Peptide Atlas. The environment and gene-regulatory influence network (EGRIN) model of the strain was constructed from a compendium of transcriptome data that was collected over 58 different steady-state and time course experiments that were performed in chemostats or batch cultures, under a spectrum of environmental perturbations that modulated methanogenesis. Analyses of the EGRIN model have revealed novel components of methanogenesis that included at least three additional protein-coding genes of previously unknown function as well as one non-coding RNA. We discovered that at least five regulatory mechanisms act in a combinatorial scheme to inter-coordinate key steps of methanogenesis with different processes such as motility, ATP biosynthesis, and carbon assimilation. Through a combination of genetic and environmental perturbation experiments we have validated the EGRIN-predicted role of two novel transcription factors in the regulation of phosphate-dependent repression of formate dehydrogenase a key enzyme in the methanogenesis pathway. The EGRIN model demonstrates regulatory affiliations within methanogenesis as well as between methanogenesis and other cellular functions. In addition, we have published an analysis of transcriptome architecture in M. maripaludis and an analysis of the effects of H 2 and formate on growth yield and regulation of methanogenesis in M. maripaludis.

59 BASIC BIOLOGICAL SCIENCES↗

Delayed leaf greening involves a major shift in the expression of cytosolic and mitochondrial ribosomes to plastid ribosomes in the highly phosphorus-use-efficient Hakea prostrata (Proteaceae)

Abstract Background and aims Hakea prostrata (Proteaceae) is a highly phosphorus-use-efficient plant native to southwest Australia. It maintains a high photosynthetic rate at low leaf phosphorus (P) and exhibits delayed leaf greening, a convergent adaptation that increases nutrient-use efficiency. This study aimed to provide broad physiological and gene expression profiles across leaf development, uncovering pathways leading from young leaves as nutrient sinks to mature leaves as low-nutrient, energy-transducing sources. Methods To explore gene expression underlying delayed greening, we analysed a de novo transcriptome for H. prostrata across five stages of leaf development. Photosynthesis and respiration rates, and foliar pigment, P and nitrogen (N) concentrations were determined, including the division of P into five biochemical fractions. Key results Transcripts encoding functions associated with leaf structure generally decreased in abundance across leaf development, concomitant with decreases in foliar concentrations of 85% for anthocyanins, 90% for P and 70% for N. The expression of genes associated with photosynthetic function increased during or after leaf expansion, in parallel with increases in photosynthetic pigments and activity, much later in leaf development than in species that do not have delayed greening. As leaves developed, transcript abundance for cytosolic and mitochondrial ribosomal proteins generally declined, whilst transcripts for chloroplast ribosomal proteins increased. Conclusions There was a much longer temporal separation of leaf cell growth from chloroplast development in H. prostrata than is found in species that lack delayed greening. Transcriptome-guided analysis of leaf development in H. prostrata provided insight into delayed greening as a nutrient-saving strategy in severely phosphorus-impoverished landscapes.

59 BASIC BIOLOGICAL SCIENCES↗

PDGF family function and prognostic value in tumor biology

Highlights: • Large scale transcriptomic data analysis reveals tumor-specific roles of PDGF signaling. • Functional gene sets associated with PDGF expression are conserved between PDGF family members. • PDGF related gene signatures have increased prognostic value over each single gene. The development and progression of a tumor depends on the close interaction of malignant cells and the supportive and suppressive tumor microenvironment. Paracrine signaling enables tumor cells to shape the surrounding tissue in order to decrease recognition by the immune system, attract blood vessels to fuel growth, change metabolic programs, and induce wound healing programs. In this study, we investigate the role of the platelet-derived growth factor (PDGF) family members PDGFA, PDGFB, PDGFC and PDGFD and their cognate tyrosine kinase receptors PDGFRA and PDGFRB, using publicly available data from The Cancer Genome Atlas and the Human Protein Atlas. Large scale analysis of expression correlation in RNA sequencing data from 7616 samples derived from 16 tumor types, revealed conserved functional programs in PDGF signaling in the majority of solid tumor types. Besides the well-known effects of PDGF signaling in mesenchymal cells, our analyses revealed a potential role of PDGF signaling in the composition of the immune microenvironment. We furthermore derived gene signatures with increased prognostic value for each PDGF family member. This study emphasizes the potential to impinge on specific paracrine signaling events to interfere with the crosstalk between malignant cells and their microenvironment.

60 APPLIED LIFE SCIENCES↗

Advances in mass spectrometry-enabled multiomics at single-cell resolution

We report biological organisms are multifaceted, intricate systems where slight perturbations can result in extensive changes in gene expression, protein abundance and/or activity, and metabolic flux. These changes occur at different timescales, spatially across cells of heterogeneous origins, and within single-cells. Hence, multimodal measurements at the smallest biological scales are necessary to capture dynamic changes in heterogeneous biological systems. Of the analytical techniques used to measure biomolecules, mass spectrometry (MS) has proven to be a powerful option due to its sensitivity, robustness, and flexibility with regard to the breadth of biomolecules that can be analyzed. Recently, many studies have coupled MS to other analytical techniques with the goal of measuring multiple modalities from the same single-cell. It is with these concepts in mind that we focus this review on MS-enabled multiomic measurements at single-cell or near-single- cell resolution.

47 OTHER INSTRUMENTATION↗

Current understanding of the human microbiome

Our understanding of the link between the human microbiome and disease, including obesity, inflammatory bowel disease, arthritis and autism, is rapidly expanding. Improvements in the throughput and accuracy of DNA sequencing of the genomes of microbial communities associated with human samples, complemented by analysis of transcriptomes, proteomes, metabolomes and immunomes, and mechanistic experiments in model systems, have vastly improved our ability to understand the structure and function of the microbiome in both diseased and healthy states. However, many challenges remain. In this Review we focus on studies in humans to describe these challenges, and propose strategies that leverage existing knowledge to move rapidly from correlation to causation, and ultimately to translation.

Gilbert, Jack A.↗

Oxidation and cyclization of casbene in the biosynthesis of Euphorbia factors from mature seeds of Euphorbia lathyris L.

Significance Ingenol mebutate is a diterpene ester with a highly complex macrocyclic structure that has been approved for the treatment of actinic keratosis, a precondition of skin cancer. The current production of ingenol mebutate through plant extraction or chemical synthesis is inefficient and costly. Here, we describe the discovery of a biosynthetic route in Euphorbia lathyris L. (caper spurge) in which regio-specific oxidation of casbene is followed by an unconventional cyclization to yield jolkinol C, a probable key intermediate in the biosynthesis of macrocyclic diterpenes, including ingenol mebutate. These results can facilitate the biotechnological production of this high-value pharmaceutical and discovery of new biosynthetic intermediates with important bioactivities.

59 BASIC BIOLOGICAL SCIENCES↗

The carbon starvation response of the ectomycorrhizal fungus Paxillus involutus

The amounts of carbon allocated to the fungal partner in ectomycorrhizal associations can vary substantially depending on the plant growth and the soil nutrient conditions, and the fungus may frequently be confronted with limitations in carbon. We used chemical analysis and transcriptome profiling to examine the physiological response of the ectomycorrhizal fungus Paxillus involutus to carbon starvation during axenic cultivation. Carbon starvation induced a decrease in the biomass. Concomitantly, ammonium, cell wall material (chitin) and proteolytic enzymes were released into the medium, which suggest autolysis. Compared with the transcriptome of actively growing hyphae, about 45% of the transcripts analyzed were differentially regulated during C-starvation. Induced during starvation were transcripts encoding extracellular enzymes such as peptidases, chitinases and laccases. In parallel, transcripts of N-transporters were upregulated, which suggest that some of the released nitrogen compounds were re-assimilated by the mycelium. The observed changes suggest that the carbon starvation response in P. involutus is associated with complex cellular changes that involves autolysis, recycling of intracellular compounds by autophagy and reabsorption of the extracellular released material. The study provides molecular markers that can be used to examine the role of autolysis for the turnover and survival of the ectomycorrhizal mycelium in soils.

59 BASIC BIOLOGICAL SCIENCES↗