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At least 163 records · Page 9

Deletion of Carboxypeptidase E in β-Cells Disrupts Proinsulin Processing but Does Not Lead to Spontaneous Development of Diabetes in Mice

Carboxypeptidase E (CPE) facilitates the conversion of prohormones into mature hormones and is highly expressed in multiple neuroendocrine tissues. Carriers of CPE mutations have elevated plasma proinsulin and develop severe obesity and hyperglycemia. We aimed to determine whether loss of Cpe in pancreatic β-cells disrupts proinsulin processing and accelerates development of diabetes and obesity in mice. Pancreatic β-cell–specific Cpe knockout mice (βCpeKO; Cpe fl/fl x Ins1 Cre/+ ) lack mature insulin granules and have elevated proinsulin in plasma; however, glucose-and KCl-stimulated insulin secretion in βCpeKO islets remained intact. High-fat diet–fed βCpeKO mice showed weight gain and glucose tolerance comparable with those of Wt littermates. Notably, β-cell area was increased in chow-fed βCpeKO mice and β-cell replication was elevated in βCpeKO islets. Transcriptomic analysis of βCpeKO β-cells revealed elevated glycolysis and Hif1α-target gene expression. On high glucose challenge, β-cells from βCpeKO mice showed reduced mitochondrial membrane potential, increased reactive oxygen species, reduced MafA, and elevated Aldh1a3 transcript levels. Following multiple low-dose streptozotocin injections, βCpeKO mice had accelerated development of hyperglycemia with reduced β-cell insulin and Glut2 expression. In conclusion, these findings suggest that Cpe and proper proinsulin processing are critical in maintaining β-cell function during the development of hyperglycemia.

59 BASIC BIOLOGICAL SCIENCES↗

Genomic and transcriptomic characterization of carbohydrate-active enzymes in the anaerobic fungus Neocallimastix cameroonii var. constans

Anaerobic gut fungi effectively degrade lignocellulose in the guts of large herbivores, but there remain a limited number of isolated, publicly available, and sequenced strains that impede our understanding of the role of anaerobic fungi within microbial communities. We isolated and characterized a new fungal isolate, Neocallimastix cameroonii var. constans, providing a transcriptomic and genomic understanding of its ability to degrade diverse carbohydrates. This anaerobic fungal strain was stably cultivated for multiple years in vitro among members of an initial enrichment microbial community derived from goat feces, and it demonstrated the ability to pair with other microbial members, namely, archaeal methanogens to produce methane from lignocellulose. Genomic analysis revealed a higher number of predicted carbohydrate-active enzymes encoded in the N. cameroonii var. constans genome compared to most other sequenced anaerobic fungi. The carbohydrate-active enzyme profile for this isolate contained 660 glycoside hydrolases, 160 carbohydrate esterases, 194 glycosyltransferases, and 85 polysaccharide lyases. Differential gene expression analysis showed the upregulation of thousands of genes (including predicted carbohydrate-active enzymes) when N. cameroonii var. constans was grown on lignocellulose (reed canary grass) compared to less complex substrates, such as cellulose (filter paper), cellobiose, and glucose. AlphaFold was used to predict functions of transcriptionally active yet poorly annotated genes, revealing feruloyl esterases that likely play an important role in lignocellulose degradation by anaerobic fungi. The combination of this strain's genomic and transcriptomic characterization, omics-informed structural prediction, and robustness in microbial co-culture make it a well-suited platform to conduct future investigations into bioprocessing and enzyme discovery.

CAZymes↗

Dissecting the metabolic reprogramming of maize root under nitrogen-deficient stress conditions

The growth and development of maize (Zea mays L.) largely depends on its nutrient uptake through the root. Hence, studying its growth, response, and associated metabolic reprogramming to stress conditions is becoming an important research direction. A genome-scale metabolic model (GSM) for the maize root was developed to study its metabolic reprogramming under nitrogen stress conditions. The model was reconstructed based on the available information from KEGG, UniProt, and MaizeCyc. Transcriptomics data derived from the roots of hydroponically grown maize plants were used to incorporate regulatory constraints in the model and simulate nitrogen-non-limiting (N+) and nitrogen-deficient (N-) condition. Model-predicted flux-sum variability analysis achieved 70% accuracy compared with the experimental change of metabolite levels. In addition to predicting important metabolic reprogramming in central carbon, fatty acid, amino acid, and other secondary metabolism, maize root GSM predicted several metabolites (l-methionine, l-asparagine, l-lysine, cholesterol, and l-pipecolate) playing a regulatory role in the root biomass growth. Furthermore, this study revealed eight phosphatidylcholine and phosphatidylglycerol metabolites which, even though not coupled with biomass production, played a key role in the increased biomass production under N-deficient conditions. Overall, the omics-integrated GSM provides a promising tool to facilitate stress condition analysis for maize root and engineer better stress-tolerant maize genotypes.

Plant Sciences↗

Comparative Phenotyping of Two Commonly Used Chlamydomonas reinhardtii Background Strains: CC-1690 (21gr) and CC-5325 (The CLiP Mutant Library Background)

The unicellular green alga Chlamydomonas reinhardtii is an excellent model organism to investigate many essential cellular processes in photosynthetic eukaryotes. Two commonly used background strains of Chlamydomonas are CC-1690 and CC-5325. CC-1690, also called 21gr, has been used for the Chlamydomonas genome project and several transcriptome analyses. CC-5325 is the background strain for the Chlamydomonas Library Project (CLiP). Photosynthetic performance in CC-5325 has not been evaluated in comparison with CC-1690. Additionally, CC-5325 is often considered to be cell-wall deficient, although detailed analysis is missing. The circadian rhythms in CC-5325 are also unclear. To fill these knowledge gaps and facilitate the use of the CLiP mutant library for various screens, we performed phenotypic comparisons between CC-1690 and CC-5325. Our results showed that CC-5325 grew faster heterotrophically in dark and equally well in mixotrophic liquid medium as compared to CC-1690. CC-5325 had lower photosynthetic efficiency and was more heat-sensitive than CC-1690. Furthermore, CC-5325 had an intact cell wall which had comparable integrity to that in CC-1690 but appeared to have reduced thickness. Additionally, CC-5325 could perform phototaxis, but could not maintain a sustained circadian rhythm of phototaxis as CC1690 did. Finally, in comparison to CC-1690, CC-5325 had longer cilia in the medium with acetate but slower swimming speed in the medium without nitrogen and acetate. Our results will be useful for researchers in the Chlamydomonas community to choose suitable background strains for mutant analysis and employ the CLiP mutant library for genome-wide mutant screens under appropriate conditions, especially in the areas of photosynthesis, thermotolerance, cell wall, and circadian rhythms.

59 BASIC BIOLOGICAL SCIENCES↗

Genome-wide transcriptional regulation in Saccharomyces cerevisiae in response to carbon dioxide

Sugar metabolism by Saccharomyces cerevisiae produces ample amounts of CO 2 under both aerobic and anaerobic conditions. High solubility of CO 2 in fermentation media, contributing to enjoyable sensory properties of sparkling wine and beers by S. cerevisiae, might affect yeast metabolism. To elucidate the overlooked effects of CO 2 on yeast metabolism, we examined glucose fermentation by S. cerevisiae under CO 2 as compared to N 2 and O 2 limited conditions. While both CO 2 and N 2 conditions are considered anaerobic, less glycerol and acetate but more ethanol were produced under CO 2 condition. Transcriptomic analysis revealed that significantly decreased mRNA levels of GPP1 coding for glycerol-3-phosphate phosphatase in glycerol synthesis explained the reduced glycerol production under CO 2 condition. Besides, transcriptional regulations in signal transduction, carbohydrate synthesis, heme synthesis, membrane and cell wall metabolism, and respiration were detected in response to CO 2 . Interestingly, signal transduction was uniquely regulated under CO 2 condition, where upregulated genes (STE3, MSB2, WSC3, STE12, and TEC1) in the signal sensors and transcriptional factors suggested that MAPK signaling pathway plays a critical role in CO 2 sensing and CO 2 -induced metabolisms in yeast. Furthermore, our study identifies CO 2 as an external stimulus for modulating metabolic activities in yeast and a transcriptional effector for diverse applications.

59 BASIC BIOLOGICAL SCIENCES↗

Transportome remodeling of a symbiotic microalga inside a planktonic host

Abstract Metabolic exchange is one of the foundations of symbiotic associations between organisms and is a driving force in evolution. In the ocean, photosymbiosis between heterotrophic hosts and microalgae is powered by photosynthesis and relies on the transfer of organic carbon to the host (e.g. sugars). Yet, the identity of transferred carbohydrates as well as the molecular mechanisms that drive this exchange remain largely unknown, especially in unicellular photosymbioses that are widespread in the open ocean. Combining genomics, single-holobiont transcriptomics, and environmental metatranscriptomics, we revealed the transportome of the marine microalga Phaeocystis in symbiosis within acantharia, with a focus on sugar transporters. At the genomic level, the sugar transportome of Phaeocystis is comparable to non-symbiotic haptophytes. By contrast, we found significant remodeling of the expression of the transportome in symbiotic microalgae compared to the free-living stage. More particularly, 36% of sugar transporter genes were differentially expressed. Several of them, such as GLUTs, TPTs, and aquaporins, with glucose, triose-phosphate sugars, and glycerol as potential substrates, were upregulated at the holobiont and community level. We also showed that algal sugar transporter genes exhibit distinct temporal expression patterns during the day. This reprogramed transportome indicates that symbiosis has a major impact on sugar fluxes within and outside the algal cell, and highlights the complexity and the dynamics of metabolic exchanges between partners. This study improves our understanding of the molecular players of the metabolic connectivity underlying the ecological success of planktonic photosymbiosis and paves the way for more studies on transporters across photosymbiotic models.

Environmental Sciences & Ecology↗

Integrated transcriptomic and metabolomic investigation of the genes and metabolites involved in swine follicular cyst formation

Follicular cysts are a common reproductive disorder in mammals that is usually caused by stress. However, the pathogenesis of follicular cysts in sows remains unclear. To provide new insights into the mechanisms of follicular cyst formation in pigs, we conducted a combined transcriptomic and metabolomic analysis on theca interna and mural granulosa cells of follicular cysts and mature follicles. We identified 2,533 up-regulated and 1,355 down-regulated genes in follicular cysts, compared with mature follicles. These differentially expressed genes were mainly found in signaling pathways related to tumor formation and cortisol synthesis and secretion as shown by Ingenuity Pathway Analysis, which predicted 4,362 upstream regulatory factors. The combined gene expression and pathway analysis identified the following genes as potential biomarkers for porcine follicular cysts: cytochrome P450 family 2 subfamily C polypeptide 18, L-lactate dehydrogenase, carbamoyl-phosphate synthase, fibroblast growth factor 7, integrin binding sialoprotein, interleukin 23 receptor, prolactin receptor, epiregulin, interleukin 1 receptor type II, arginine vasopressin receptor 1A, fibroblast growth factor 10, claudin 7, G Protein Subunit Gamma 3, cholecystokinin B receptor and cytosolic phospholipase A2 . Metabolomics analysis found significant differences in 87 metabolites, which were enriched in unsaturated fatty acid biosynthesis, and sphingolipid signaling pathways. These results provide valuable information on the molecular mechanisms of follicular cyst formation, which may facilitate the development of new therapeutics to prevent and treat follicular cysts.

Dai, Jiage↗

Metabolomic and transcriptomic remodeling of bone marrow myeloid cells in response to maternal obesity

Maternal obesity puts the offspring at high risk of developing obesity and cardiometabolic diseases in adulthood. Here, we utilized a mouse model of maternal high-fat diet (HFD)-induced obesity that recapitulates metabolic perturbations seen in humans. We show increased adiposity in the offspring of HFD-fed mothers (Off-HFD) when compared with the offspring of regular diet-fed mothers (Off-RD). We have previously reported significant immune perturbations in the bone marrow of newly weaned Off-HFD. Here, we hypothesized that lipid metabolism is altered in the bone marrow of Off-HFD versus Off-RD. To test this hypothesis, we investigated the lipidomic profile of bone marrow cells collected from 3-week-old Off-RD and Off-HFD. Diacylglycerols (DAGs), triacylglycerols (TAGs), sphingolipids, and phospholipids were remarkably different between the groups, independent of fetal sex. Levels of cholesteryl esters were significantly decreased in Off-HFD, suggesting reduced delivery of cholesterol. These were accompanied by age-dependent progression of mitochondrial dysfunction in bone marrow cells. We subsequently isolated CD11b+ myeloid cells from 3-wk-old mice and conducted metabolomic, lipidomic, and transcriptomic analyses. The lipidomic profiles of myeloid cells were similar to those of bone marrow cells and included increases in DAGs and decreased TAGs. Transcriptomics revealed altered expression of genes related to immune pathways, including macrophage alternative activation, B-cell receptors, and transforming growth factor-β signaling. All told, this study revealed lipidomic, metabolomic, and gene expression abnormalities in bone marrow cells broadly, and in bone marrow myeloid cells particularly, in the newly weaned offspring of mothers with obesity, which might at least partially explain the progression of metabolic and cardiovascular diseases in their adulthood.

RNA sequencing↗

Genetic and behavioral adaptation of Candida parapsilosis to the microbiome of hospitalized infants revealed by in situ genomics, transcriptomics, and proteomics

Background Candida parapsilosis is a common cause of invasive candidiasis, especially in newborn infants, and infections have been increasing over the past two decades. C. parapsilosis has been primarily studied in pure culture, leaving gaps in understanding of its function in a microbiome context. Results. Here, we compare five unique C. parapsilosis genomes assembled from premature infant fecal samples, three of which are newly reconstructed, and analyze their genome structure, population diversity, and in situ activity relative to reference strains in pure culture. All five genomes contain hotspots of single nucleotide variants, some of which are shared by strains from multiple hospitals. A subset of environmental and hospital-derived genomes share variants within these hotspots suggesting derivation of that region from a common ancestor. Four of the newly reconstructed C. parapsilosis genomes have 4 to 16 copies of the gene RTA3, which encodes a lipid translocase and is implicated in antifungal resistance, potentially indicating adaptation to hospital antifungal use. Time course metatranscriptomics and metaproteomics on fecal samples from a premature infant with a C. parapsilosis blood infection revealed highly variable in situ expression patterns that are distinct from those of similar strains in pure cultures. For example, biofilm formation genes were relatively less expressed in situ, whereas genes linked to oxygen utilization were more highly expressed, indicative of growth in a relatively aerobic environment. In gut microbiome samples, C. parapsilosis co-existed with Enterococcus faecalis that shifted in relative abundance over time, accompanied by changes in bacterial and fungal gene expression and proteome composition. Conclusions The results reveal potentially medically relevant differences in Candida function in gut vs. laboratory environments, and constrain evolutionary processes that could contribute to hospital strain persistence and transfer into premature infant microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗

High throughput single cell multiomics platform [Abstract]

In this collaborative project, PNNL and Scienion will co-develop an integrated microfluidic technology to co-measure the transcriptome and proteome in single cells. The technology will enable us to efficiently separate proteins from mRNA transcripts between two microchips, barcode the molecules, and measure them separately with next-generation sequencing and mass spectrometry, respectively. Multicellular organisms contain diverse cell types and tremendous cell-to-cell heterogeneity that dictates a multitude of biological functions in both physiological and pathological environments. Even in the case of microbes, these genetically identical organisms can randomly differentiate into many subpopulations that assume different roles for the survival of the community. Bulk-scale measurements are insufficient to resolve such complexities. The development and applications of high throughput single-cell omics technologies have transformed our understanding of cellular heterogeneities and their differential responses to internal signaling events or external stimulations. Despite these advances, most current single-cell omic technologies provide information on only one type of biomolecule. Perse, such measurements provide incomplete information because the cell phenotype is determined by multiple layers of biomolecules and the interplay between genome, epigenome, transcriptome, and proteome. For example, mRNA abundance in one cell can not be precisely referred to the corresponding DNA and protein in other cells because of the potential subtle difference in genotype (e.g., somatic mutation or copy number variation) or phenotype (external microenvironment and cell-cell interactions). As such, parallel measurement of multiple biomolecules in the same single cells can offer unique advantages compared with measuring them separately in different single cells. Scienion is a world-leading biotech company focusing on precision liquid handling and its application in single-cell whole-genome sequencing and RNA sequencing. PNNL is the leading institution in ultrasensitive mass spectrometry, microfluidics, and untargeted single-cell proteomics (scProteomics). This collaboration will facilitate a unique fusion between scTranscriptomics capability at Scienion and scProteomics capabilities at PNNL to, for the first time, perform both untargeted transcriptomics and proteomics from the same single cells.

59 BASIC BIOLOGICAL SCIENCES↗

Comparative Molecular Analysis of Cancer Behavior Cultured In Vitro, In Vivo, and Ex Vivo

Current pre-clinical models of cancer fail to recapitulate the cancer cell behavior in primary tumors primarily because of the lack of a deeper understanding of the effects that the microenvironment has on cancer cell phenotype. Transcriptomic profiling of 4T1 murine mammary carcinoma cells from 2D and 3D cultures, subcutaneous or orthotopic allografts (from immunocompetent or immunodeficient mice), as well as ex vivo tumoroids, revealed differences in molecular signatures including altered expression of genes involved in cell cycle progression, cell signaling and extracellular matrix remodeling. The 3D culture platforms had more in vivo-like transcriptional profiles than 2D cultures. In vivo tumors had more cells undergoing epithelial-to-mesenchymal transition (EMT) while in vitro cultures had cells residing primarily in an epithelial or mesenchymal state. Ex vivo tumoroids incorporated aspects of in vivo and in vitro culturing, retaining higher abundance of cells undergoing EMT while shifting cancer cell fate towards a more mesenchymal state. Cellular heterogeneity surveyed by scRNA-seq revealed that ex vivo tumoroids, while rapidly expanding cancer and fibroblast populations, lose a significant proportion of immune components. This study emphasizes the need to improve in vitro culture systems and preserve syngeneic-like tumor composition by maintaining similar EMT heterogeneity as well as inclusion of stromal subpopulations.

59 BASIC BIOLOGICAL SCIENCES↗

Plant Metabolic Network 15: A resource of genome-wide metabolism databases for 126 plants and algae

To understand and engineer plant metabolism, we need a comprehensive and accurate annotation of all metabolic information across plant species. As a step towards this goal, we, in this study, generated genome-scale metabolic pathway databases of 126 algal and plant genomes, ranging from model organisms to crops to medicinal plants (https://plantcyc.org). Of these, 104 have not been reported before. We systematically evaluated the quality of the databases, which revealed that our semi-automated validation pipeline dramatically improves the quality. We then compared the metabolic content across the 126 organisms using multiple correspondence analysis and found that Brassicaceae, Poaceae, and Chlorophyta appeared as metabolically distinct groups. To demonstrate the utility of this resource, we used recently published sorghum transcriptomics data to discover previously unreported trends of metabolism underlying drought tolerance. We also used single-cell transcriptomics data from the Arabidopsis root to infer cell type-specific metabolic pathways. This work shows the quality and quantity of our resource and demonstrates its wide-ranging utility in integrating metabolism with other areas of plant biology.

59 BASIC BIOLOGICAL SCIENCES↗

Cyanobacterial circadian regulation enhances bioproduction under subjective nighttime through rewiring of carbon partitioning dynamics, redox balance orchestration, and cell cycle modulation

Abstract Background The industrial feasibility of photosynthetic bioproduction using cyanobacterial platforms remains challenging due to insufficient yields, particularly due to competition between product formation and cellular carbon demands across different temporal phases of growth. This study investigates how circadian clock regulation impacts carbon partitioning between storage, growth, and product synthesis in Synechococcus elongatus PCC 7942, and provides insights that suggest potential strategies for enhanced bioproduction. Results After entrainment to light-dark cycles, PCC 7942 cultures transitioned to constant light revealed distinct temporal patterns in sucrose production, exhibiting three-fold higher productivity during subjective night compared to subjective day despite moderate down-regulation of genes from the photosynthetic apparatus. This enhanced productivity coincided with reduced glycogen accumulation and halted cell division at subjective night time, suggesting temporal separation of competing processes. Transcriptome analysis revealed coordinated circadian clock-driven adjustment of the cell cycle and rewiring of energy and carbon metabolism, with over 300 genes showing differential expression across four time points. The subjective night was characterized by altered expression of cell division-related genes and reduced expression of genes involved in glycogen synthesis, while showing upregulation of glycogen degradation pathways, alternative electron flow components, the pentose phosphate pathway, and oxidative decarboxylation of pyruvate. These molecular changes created favorable conditions for product formation through enhanced availability of major sucrose precursors (glucose-1-phosphate and fructose-6-phosphate) and maintained redox balance through multiple mechanisms. Conclusions Our analysis of circadian regulatory rewiring of carbon metabolism and redox balancing suggests two potential approaches that could be developed for improving cyanobacterial bioproduction: leveraging natural circadian rhythms for optimizing cultivation conditions and timing of pathway induction, and engineering strains that mimic circadian-driven metabolic shifts through controlled carbon flux redistribution and redox rebalancing. While these strategies remain to be tested, they could theoretically improve the efficiency of photosynthetic bioproduction by enabling better temporal separation between cell growth, carbon storage accumulation, and product synthesis phases.

59 BASIC BIOLOGICAL SCIENCES↗

Phylogenetically diverse wild plant species use common biochemical strategies to thrive in the Atacama Desert

The best ideotypes are under mounting pressure due to increased aridity. Understanding the conserved molecular mechanisms that evolve in wild plants adapted to harsh environments is crucial in developing new strategies for agriculture. Yet our knowledge of such mechanisms in wild species is scant. We performed metabolic pathway reconstruction using transcriptome information from 32 Atacama and phylogenetically related species that do not live in Atacama (sister species). We analyzed reaction enrichment to understand the commonalities and differences of Atacama plants. To gain insights into the mechanisms that ensure survival, we compared expressed gene isoform numbers and gene expression patterns between the annotated biochemical reactions from 32 Atacama and sister species. We found biochemical convergences characterized by reactions enriched in at least 50% of the Atacama species, pointing to potential advantages against drought and nitrogen starvation, for instance. Furthermore, these findings suggest that the adaptation in the Atacama Desert may result in part from shared genetic legacies governing the expression of key metabolic pathways to face harsh conditions. Enriched reactions corresponded to ubiquitous compounds common to extreme and agronomic species and were congruent with our previous metabolomic analyses. Convergent adaptive traits offer promising candidates for improving abiotic stress resilience in crop species.

59 BASIC BIOLOGICAL SCIENCES↗

Shade signals alter the expression of circadian clock genes in newly-formed bioenergy sorghum internodes

Stem internodes of bioenergy sorghum inbred R.07020 are longer at high plant density (shade) than at low plant density (control). Initially, the youngest newly-formed subapical stem internodes of shade-treated and control plants are comparable in length. However, full-length internodes of shade-treated plants are three times longer than the internodes of the control plants. To identify the early molecular events associated with internode elongation in response to shade, we analyzed the transcriptome of the newly-formed internodes of shade-treated and control plants sampled between 4 and 6 hr after the start of the light period (14 hr light/10 hr dark). Sorghum genes homologous to the Arabidopsis shade marker genes ATHB2 and PIL1 were not differentially expressed. The results indicate that shade signals promote internode elongation indirectly because sorghum internodes are not illuminated and grow while enclosed with leaf sheaths. Sorghum genes homologous to the Arabidopsis morning-phased circadian clock genes LHY, RVE, and LNK were downregulated and evening-phased genes such as TOC1, PRR5, and GI were upregulated in young internodes in response to shade. We hypothesize that a change in the function or patterns of expression of the circadian clock genes is the earliest molecular event associated with internode elongation in response to shade in bioenergy sorghum. Increased expression of CycD1, which promotes cell division, and decreased expression of cell wall-loosening and MBF1-like genes, which promote cell expansion, suggest that shade signals promote internode elongation in bioenergy sorghum in part through increasing cell number by delaying transition from cell division to cell expansion.

54 ENVIRONMENTAL SCIENCES↗

Metabolism of Scenedesmus obliquus cultivated with raw plant substrates

The potential benefits of adding raw, non-food, lignocellulosic plant material as a carbon source for mixotrophic growth of microalgae have previously been demonstrated. This approach has advantages over using traditional carbon sources like glucose or acetate due to wide-spread plant biomass availability and substrate recalcitrance to bacterial contamination. Here, we report the overall growth characteristics and explore the metabolic patterns of Scenedesmus obliquus cultured in the presence raw plant substrate. An initial screen of plant substrate candidates showed an increase in specific growth rate and biomass accumulation when S. obliquus was cultured in the presence of switchgrass or yard waste compared to media alone. We observed a near doubling of microalgal dry weight when S. obliquus was grown with 0.2% ( w/v ) switchgrass under ambient CO 2 . Scanning electron microscopy (SEM) of corn stem after S. obliquus cultivation exhibited substantial phloem degradation. Transcriptomic analyses of S. obliquus during mid- and late-log phase growth revealed a dynamic metabolic landscape within many KEGG pathways. Notably, differential expression was observed for several potential glycosyl hydrolases. We also investigated the influence of switchgrass on the growth of S. obliquus at 50 L volume in mini raceway ponds to determine the scalability of this approach.

Schambach, Jenna Y.↗

Temporal regulation of cold transcriptional response in switchgrass

Switchgrass low-land ecotypes have significantly higher biomass but lower cold tolerance compared to up-land ecotypes. Understanding the molecular mechanisms underlying cold response, including the ones at transcriptional level, can contribute to improving tolerance of high-yield switchgrass under chilling and freezing environmental conditions. Here, by analyzing an existing switchgrass transcriptome dataset, the temporal cis- regulatory basis of switchgrass transcriptional response to cold is dissected computationally. We found that the number of cold-responsive genes and enriched Gene Ontology terms increased as duration of cold treatment increased from 30 min to 24 hours, suggesting an amplified response/cascading effect in cold-responsive gene expression. To identify genomic sequences likely important for regulating cold response, machine learning models predictive of cold response were established using k -mer sequences enriched in the genic and flanking regions of cold-responsive genes but not non-responsive genes. These k -mers, referred to as putative cis -regulatory elements (pCREs) are likely regulatory sequences of cold response in switchgrass. There are in total 655 pCREs where 54 are important in all cold treatment time points. Consistent with this, eight of 35 known cold-responsive CREs were similar to top-ranked pCREs in the models and only these eight were important for predicting temporal cold response. More importantly, most of the top-ranked pCREs were novel sequences in cold regulation. Our findings suggest additional sequence elements important for cold-responsive regulation previously not known that warrant further studies.

60 APPLIED LIFE SCIENCES↗

Accurate flux predictions using tissue-specific gene expression in plant metabolic modeling

The accurate prediction of complex phenotypes such as metabolic fluxes in living systems is a grand challenge for systems biology and central to efficiently identifying biotechnological interventions that can address pressing industrial needs. The application of gene expression data to improve the accuracy of metabolic flux predictions using mechanistic modeling methods such as flux balance analysis (FBA) has not been previously demonstrated in multi-tissue systems, despite their biotechnological importance. We hypothesized that a method for generating metabolic flux predictions informed by relative expression levels between tissues would improve prediction accuracy. Relative gene expression levels derived from multiple transcriptomic and proteomic datasets were integrated into FBA predictions of a multi-tissue, diel model of Arabidopsis thaliana’s central metabolism. This integration dramatically improved the agreement of flux predictions with experimentally based flux maps from 13 C metabolic flux analysis compared with a standard parsimonious FBA approach. Disagreement between FBA predictions and MFA flux maps was measured using weighted averaged percent error values, and for parsimonious FBA this was 169%–180% for high light conditions and 94%–103% for low light conditions, depending on the gene expression dataset used. This fell to 10%-13% and 9%-11% upon incorporating expression data into the modeling process, which also substantially altered the predicted carbon and energy economy of the plant.

59 BASIC BIOLOGICAL SCIENCES↗