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At least 775 records · Page 43

Early Transcriptomic Changes in the Ileal Pouch Provide Insight into the Molecular Pathogenesis of Pouchitis and Ulcerative Colitis

Background: Ulcerative colitis (UC) only involves the colonic mucosa. Yet, nearly 50% of patients with UC who undergo total proctocolectomy with ileal pouch anal anastomosis develop UC-like inflammation of the ileal pouch (pouchitis). By contrast, patients with familial adenomatous polyposis (FAP) with ileal pouch anal anastomosis develop pouchitis far less frequently. We hypothesized that pathogenic events associated with the development of UC are recapitulated by colonic-metaplastic transcriptomic reprogramming of the UC pouch. Methods: We prospectively sampled pouch and prepouch ileum mucosal biopsies in patients with UC with ileal pouch anal anastomosis 4, 8, and 12 months after their pouch was in continuity. Mucosal samples were also obtained from patients with FAP. Transcriptional profiles of the UC and FAP pouch and prepouch ileum were investigated via RNA sequencing and compared with data from a previously published microarray study. Results: Unlike patients with FAP, subjects with UC exhibited a large set of differentially expressed genes between the pouch and prepouch ileum as early as 4 months after pouch functionalization. Functional pathway analysis of differentially expressed genes in the UC pouch revealed an enhanced state of immune/inflammatory response and extracellular matrix remodeling. Moreover, >70% of differentially expressed genes mapped to published inflammatory bowel diseases microarray data sets displayed directional changes consistent with active UC but not with Crohn's disease. Conclusions: The UC pouch, well before histologic inflammation, already displays a systems-level gain of colon-associated genes and loss of ileum-associated genes. Patients with UC exhibit a unique transcriptomic response to ileal pouch creation that can be observed well before disease and may in part explain their susceptibility to the development of pouchitis.

familial adenomatous polyposis↗

MODE: A Web Application for Interactive Visualization and Exploration of Omics Data

Studies generating transcriptomics, proteomics, lipidomics, and metabolomics (colloquially referred to as “omics”) data allow researchers to find biomarkers or molecular targets, or understand complex biological structures and functions by identifying changes in biomolecule abundance and expression between experimental conditions. Omics data is multi-dimensional and oftentimes summarization techniques such as principal component analysis (PCA) are used to identify high-level patterns in data. Though useful, these summaries don’t allow exploration of detailed patterns in omics data that may have biological relevance. The use of interactive HTML displays with plots allows researchers to interact with omics data at a detailed level, but building these displays requires significant coding expertise. To overcome this barrier, the software MODE was built to empower users to build their own interactive HTML displays to support scientific discovery. These displays are easily shareable, do not depend on a specific operating system, and allow users to effortlessly sort and filter plots by categorical or numerical variables. MODE allows users to build and share these displays with several options for plot design and meta selection. In conclusion, the MODE web application and its capabilities are presented and then demonstrated on lipidomics data from a leaf wounding study.

lipidomics↗

Transcriptomic and proteomic analyses of Desulfovibrio vulgaris biofilms: Carbon and energy flow contribute to the distinct biofilm growth state

Background: Desulfovibrio vulgaris Hildenborough is a sulfate-reducing bacterium (SRB) that is intensively studied in the context of metal corrosion and heavy-metal bioremediation, and SRB populations are commonly observed in pipe and subsurface environments as surface-associated populations. In order to elucidate physiological changes associated with biofilm growth at both the transcript and protein level, transcriptomic and proteomic analyses were done on mature biofilm cells and compared to both batch and reactor planktonic populations. The biofilms were cultivated with lactate and sulfate in a continuously fed biofilm reactor, and compared to both batch and reactor planktonic populations. Results: The functional genomic analysis demonstrated that biofilm cells were different compared to planktonic cells, and the majority of altered abundances for genes and proteins were annotated as hypothetical (unknown function), energy conservation, amino acid metabolism, and signal transduction. Genes and proteins that showed similar trends in detected levels were particularly involved in energy conservation such as increases in an annotated ech hydrogenase, formate dehydrogenase, pyruvate:ferredoxin oxidoreductase, and rnf oxidoreductase, and the biofilm cells had elevated formate dehydrogenase activity. Several other hydrogenases and formate dehydrogenases also showed an increased protein level, while decreased transcript and protein levels were observed for putative coo hydrogenase as well as a lactate permease and hyp hydrogenases for biofilm cells. Genes annotated for amino acid synthesis and nitrogen utilization were also predominant changers within the biofilm state. Ribosomal transcripts and proteins were notably decreased within the biofilm cells compared to exponential-phase cells but were not as low as levels observed in planktonic, stationary-phase cells. Several putative, extracellular proteins (DVU1012, 1545) were also detected in the extracellular fraction from biofilm cells. Conclusions: Even though both the planktonic and biofilm cells were oxidizing lactate and reducing sulfate, the biofilm cells were physiologically distinct compared to planktonic growth states due to altered abundances of genes/proteins involved in carbon/energy flow and extracellular structures. In addition, average expression values for multiple rRNA transcripts and respiratory activity measurements indicated that biofilm cells were metabolically more similar to exponential-phase cells although biofilm cells are structured differently. The characterization of physiological advantages and constraints of the biofilm growth state for sulfate-reducing bacteria will provide insight into bioremediation applications as well as microbially-induced metal corrosion.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets such as sex or age of the model organism used. In the present study, NASA GeneLab-hosted RNAseq datasets from rodent liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC, to determine statistical differences between datasets before and after correction, Principal Component Analysis, to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the standard approach. Thus, the most robust standard correction will be implemented in the GeneLab Visualization 2.0 platform when datasets are combined.

GeneLab, RNA-seq, Batch Correction↗

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the respective standard approach. Of the methods tested, standard ComBat and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

GeneLab↗

A Microbe Associated with Sleep Revealed by a Novel Systems Genetic Analysis of the Microbiome in Collaborative Cross Mice

The microbiome influences health and disease through complex networks of host genetics, genomics, microbes, and environment. Identifying the mechanisms of these interactions has remained challenging. Systems genetics in laboratory mice (Mus musculus) enables data-driven discovery of biological network components and mechanisms of host–microbial interactions underlying disease phenotypes. To examine the interplay among the whole host genome, transcriptome, and microbiome, we mapped QTL and correlated the abundance of cecal messenger RNA, luminal microflora, physiology, and behavior in a highly diverse Collaborative Cross breeding population. One such relationship, regulated by a variant on chromosome 7, was the association of Odoribacter (Bacteroidales) abundance and sleep phenotypes. In a test of this association in the BKS.Cg-Dock7 m +/+ Lepr db /J mouse model of obesity and diabetes, known to have abnormal sleep and colonization by Odoribacter, treatment with antibiotics altered sleep in a genotype-dependent fashion. The many other relationships extracted from this study can be used to interrogate other diseases, microbes, and mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗

Genome expansion and lineage-specific genetic innovations in the forest pathogenic fungi Armillaria

Armillaria species are both devastating forest pathogens and some of the largest terrestrial organisms on Earth. They forage for hosts and achieve immense colony sizes via rhizomorphs, root-like multicellular structures of clonal dispersal. Here, we sequenced and analysed the genomes of four Armillaria species and performed RNA sequencing and quantitative proteomic analysis on the invasive and reproductive developmental stages of A. ostoyae. Comparison with 22 related fungi revealed a significant genome expansion in Armillaria, affecting several pathogenicity-related genes, lignocellulose-degrading enzymes and lineage-specific genes expressed during rhizomorph development. Rhizomorphs express an evolutionarily young transcriptome that shares features with the transcriptomes of both fruiting bodies and vegetative mycelia. Several genes show concomitant upregulation in rhizomorphs and fruiting bodies and share cis-regulatory signatures in their promoters, providing genetic and regulatory insights into complex multicellularity in fungi. Our results suggest that the evolution of the unique dispersal and pathogenicity mechanisms of Armillaria might have drawn upon ancestral genetic toolkits for wood-decay, morphogenesis and complex multicellularity.

59 BASIC BIOLOGICAL SCIENCES↗

CYP76BK1 orthologs catalyze furan and lactone ring formation in clerodane diterpenoids across the mint family

The Lamiaceae (mint family) is the largest known source of furanoclerodanes, a subset of clerodane diterpenoids with broad bioactivities including insect antifeedant properties. The Ajugoideae subfamily, in particular, accumulates significant numbers of structurally related furanoclerodanes. The biosynthetic capacity for formation of these diterpenoids is retained across most Lamiaceae subfamilies, including the early-diverging Callicarpoideae which forms a sister clade to the rest of Lamiaceae. VacCYP76BK1, a cytochrome P450 monooxygenase from Vitex agnus-castus, was previously found to catalyze the formation of the proposed precursor to furan and lactone-containing labdane diterpenoids. Through transcriptome-guided pathway exploration, we identified orthologs of VacCYP76BK1 in Ajuga reptans and Callicarpa americana. Functional characterization demonstrated that both could catalyze the oxidative cyclization of clerodane backbones to yield a furan ring. Subsequent investigation revealed a total of 10 CYP76BK1 orthologs across six Lamiaceae subfamilies. Through analysis of available chromosome-scale genomes, we identified four CYP76BK1 members as syntelogs within a conserved syntenic block across divergent subfamilies. This suggests an evolutionary lineage that predates the speciation of the Lamiaceae. Functional characterization of the CYP76BK1 orthologs affirmed conservation of function, as all catalyzed furan ring formation. Additionally, some orthologs yielded two novel lactone ring moieties. The presence of the CYP76BK1 orthologs across Lamiaceae subfamilies closely overlaps with the distribution of reported furanoclerodanes. Together, the activities and distribution of the CYP76BK1 orthologs identified here support their central role in furanoclerodane biosynthesis within the Lamiaceae family. Our findings lay the groundwork for biotechnological applications to harness the economic potential of this promising class of compounds.

59 BASIC BIOLOGICAL SCIENCES↗

Stress response to CO 2 deprivation by Arabidopsis thaliana in plant cultures

After being the standard plant propagation protocol for decades, cultures of Arabidopsis thaliana sealed with Parafilm remain common today out of practicality, habit, or necessity (as in co-cultures with microorganisms). Regardless of concerns over the aeration of these cultures, no investigation has explored the CO 2 transport inside these cultures and its effect on the plants. Thereby, it was impossible to assess whether Parafilm-seals used today or in thousands of older papers in the literature constitute a treatment, and whether this treatment could potentially affect the study of other treatments.For the first time we report the CO 2 concentrations in Parafilm-sealed cultures of A. thaliana with a 1 minute temporal resolution, and the transcriptome comparison with aerated cultures. The data show significant CO 2 deprivation to the plants, a drastic suppression of photosynthesis, respiration, starch accumulation, chlorophyll biosynthesis, and an increased accumulation of reactive oxygen species. Most importantly, CO 2 deprivation occurs as soon as the cotyledons emerge. Gene expression analysis indicates a significant alteration of 35% of the pathways when compared to aerated cultures, especially in stress response and secondary metabolism processes. On the other hand, the observed increase in the production of glucosinolates and flavonoids suggests intriguing possibilities for CO 2 deprivation as an organic biofortification treatment in high-value crops.

59 BASIC BIOLOGICAL SCIENCES↗

A KBase Case Study on Genome-wide Transcriptomics and Plant Primary Metabolism in Sorghum

A better understanding of the genetic and metabolic mechanisms that confer stress resistance and tolerance in plants is key to engineering new crops through advanced breeding technologies. This requires a systems biology approach that builds on a genome-wide understanding of the regulation of gene expression, plant metabolism, physiology and growth. In this study, we examine the response to drought stress in Sorghum, as we leverage the tools for transcriptomics and plant metabolic modeling we have implemented at the U.S. Department of Energy Systems Biology Knowledgebase (KBase). KBase enables researchers worldwide to collaborate and advance research by allowing them to upload private or public data into the KBase Narrative Interface, empowering them to analyze this data using a rich, extensible array of computational and data-analytics tools, and allows them to securely share scientific workflows and conclusions. We demonstrate how to use the current RNA-seq tools in KBase, applicable to both plants and microbes, to assemble and quantify long transcripts and identify differentially expressed genes effectively. More specifically, we demonstrate the utility of the platform by identifying key genes that are differentially expressed during drought-stress in Sorghum bicolor, which is an important sustainable production crop plant. We then show how to use KBase tools to predict the membership of genes in metabolic pathways and examine expression data in the context of metabolic subsystems. We demonstrate the power of the platform by making the data analysis and interpretation available to the biologists in the reproducible, re-usable, point-and-click format of a KBase Narrative thus promoting FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles for scientific data management and stewardship.

59 BASIC BIOLOGICAL SCIENCES↗

Unlocking the distinctive enzymatic functions of the early plant biomass deconstructive genes in a brown rot fungus by cell-free protein expression

ABSTRACT Saprotrophic fungi that cause brown rot of woody biomass evolved a distinctive mechanism that relies on reactive oxygen species (ROS) to kick-start lignocellulosic polymers’ deconstruction. These ROS agents are generated at incipient decay stages through a series of redox relays that shuttle electrons from fungus’s central metabolism to extracellular Fenton chemistry. A list of genes has been suggested encoding the enzyme catalysts of the redox processes involved in ROS’s function. However, navigating the functions of the encoded enzymes has been challenging due to the lack of a rapid method for protein synthesis. Here, we employed cell-free expression system to synthesize four redox or degradative enzymes, which were identified, by transcriptomic data, as conserved players of the ROS oxidation phase across brown rot fungal species. All four enzymes were successfully expressed and showed activities that enable confident assignment of function, namely, benzoquinone reductase (BQR), ferric reductase, α-L-arabinofuranosidase (ABF), and heme-thiolate peroxidase (HTP). Detailed analysis of their catalytic features within the context of brown rot environments allowed us to interpret their roles during ROS-driven wood decomposition. Specifically, we validated the functions of BQR as the driver redox enzyme of Fenton cycles and reconstructed its interactions with the co-occurring HTP or laccase and ABF. Taken together, this research demonstrated that the cell-free expression platform is adequate for synthesizing functional fungal enzymes and provided an alternative route for the rapid characterization of fungal proteins, escalating our understanding of the distinctive biocatalyst system for plant biomass conversion. IMPORTANCE Brown rot fungi are efficient wood decomposers in nature, and their unique degradative systems harbor untapped catalysts pursued by the biorefinery and bioremediation industries. While the use of “omics” platforms has recently uncovered the key “oxidative-hydrolytic” mechanisms that allow these fungi to attack lignocellulose, individual protein characterization is lagging behind due to the lack of a robust method for rapid synthesis of crucial fungal enzymes. This work delves into the studies of biochemical functions of brown rot enzymes using a rapid, cell-free expression platform, which allowed the successful depictions of enzymes’ catalytic features, their interactions with Fenton chemistry, and their roles played during the incipient stage of brown rot when fungus sets off the reactive oxygen species for oxidative degradation. We expect this research could illuminate cell-free protein expression system’s use to fulfill the increasing need for functional studies of fungal enzymes, advancing the discoveries of novel biomass-converting catalysts.

60 APPLIED LIFE SCIENCES↗

Comparative RNA-Seq transcriptome analyses reveal dynamic time-dependent effects of 56 Fe, 16 O, and 28 Si irradiation on the induction of murine hepatocellular carcinoma

One of the health risks posed to astronauts during deep space flights is exposure to high charge, high-energy (HZE) ions (Z > 13), which can lead to the induction of hepatocellular carcinoma (HCC). However, little is known on the molecular mechanisms of HZE irradiation-induced HCC. We performed comparative RNA-Seq transcriptomic analyses to assess the carcinogenic effects of 600 MeV/n 56 Fe (0.2 Gy), 1 GeV/n 16 O (0.2 Gy), and 350 MeV/n 28 Si (0.2 Gy) ions in a mouse model for irradiation-induced HCC. C3H/HeNCrl mice were subjected to total body irradiation to simulate space environment HZE-irradiation, and liver tissues were extracted at five different time points post-irradiation to investigate the time-dependent carcinogenic response at the transcriptomic level. Our data demonstrated a clear difference in the biological effects of these HZE ions, particularly immunological, such as Acute Phase Response Signaling, B Cell Receptor Signaling, IL-8 Signaling, and ROS Production in Macrophages. Also seen in this study were novel unannotated transcripts that were significantly affected by HZE. To investigate the biological functions of these novel transcripts, we used a machine learning technique known as self-organizing maps (SOMs) to characterize the transcriptome expression profiles of 60 samples (45 HZE-irradiated, 15 non-irradiated control) from liver tissues. A handful of localized modules in the maps emerged as groups of co-regulated and co-expressed transcripts. The functional context of these modules was discovered using overrepresentation analysis. We found that these spots typically contained enriched populations of transcripts related to specific immunological molecular processes (e.g., Acute Phase Response Signaling, B Cell Receptor Signaling, IL-3 Signaling), and RNA Transcription/Expression. A large number of transcripts were found differentially expressed post-HZE irradiation. These results provide valuable information for uncovering the differences in molecular mechanisms underlying HZE specific induced HCC carcinogenesis. Additionally, a handful of novel differentially expressed unannotated transcripts were discovered for each HZE ion. Taken together, these findings may provide a better understanding of biological mechanisms underlying risks for HCC after HZE irradiation and may also have important implications for the discovery of potential countermeasures against and identification of biomarkers for HZE-induced HCC.

59 BASIC BIOLOGICAL SCIENCES↗

Open Science for Plants in Space: Data Sharing, Standards, and Informatics for Reuse and Knowledge Discovery

Upcoming deep space missions will rely on plants for crew and ecosystem health. Open access space biology data enables scientists to examine the biological responses of plants to ionizing radiation, altered gravity, low atmospheric pressure, elevated CO2, altered photoperiods and many other abiotic stressors. Open Science is the practice of making research available to all, while respecting diverse cultures, and fostering collaborations with equity. 2023 is the ‘Year of Open Science’, and NASA has a 5-year Transform to Open Science (TOPS) initiative designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) within NASA’s Biological and Physical Sciences Division provides access to data from space-relevant biological experiments. OSDR combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. GeneLab started in 2014 with the creation of the first space-relevant FAIR (Findable, Accessible, Interoperable, Reusable) biological ‘omics repository, providing detailed metadata on investigation, sample, and assay levels. The addition of ALSDA to OSDR expands plant data analysis capabilities across both phenotypic and ‘omics data. Today, OSDR hosts 62+ plant datasets and has enabled 58 peer-reviewed publications. Most of these publications were collaboration efforts under the OSDR Analysis Working Groups (AWGs). AWGs provide great opportunities for investigators to collaborate and set new standards for space-relevant data and metadata. The AWGs welcome any ASPB members interested in contributing plant expertise for space biology, and to serve as subject matter experts as we establish the framework for modern plant data archiving. Investigators are invited to submit their space-relevant plant datasets to OSDR and visit the site to learn about the tools OSDR has to offer (osdr.nasa.gov/bio).

FAIR↗

Open Science for Plants in Space: Data Sharing, Standards, and Informatics for Reuse and Knowledge Discovery

Upcoming deep space missions will rely on plants for crew and ecosystem health. Open access space biology data enables scientists to examine the biological responses of plants to ionizing radiation, altered gravity, low atmospheric pressure, elevated CO2, altered photoperiods and many other abiotic stressors. Open Science is the practice of making research available to all, while respecting diverse cultures, to foster collaborations with equity. NASA has declared 2023 as the ‘Year of Open Science’ and created a 5-year Transform to Open Science (TOPS) initiative designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) within the Biological and Physical Sciences Division provides access to data from space-relevant biological experiments. OSDR combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. GeneLab started in 2014 with the creation of the first space-relevant FAIR (Findable, Accessible, Interoperable, Reusable) biological ‘omics repository, providing detailed metadata on investigation, sample, and assay levels. The addition of ALSDA to OSDR expands plant data analysis capabilities across both phenotypic and ‘omics data. Today, OSDR hosts 62+ plant datasets and has enabled 58 peer-reviewed publications. Most of these publications were collaboration efforts under the OSDR Analysis Working Groups (AWGs). AWGs provide great opportunities for investigators to collaborate with community members and set new standards for space-relevant data and metadata. The AWGs welcome any ASGSR members interested in contributing plant expertise for space biology, and to serve as subject matter experts as we establish the framework for modern plant data archiving. Investigators are encouraged to submit their space-relevant plant datasets to OSDR and visit the site to learn about the tools OSDR has to offer (osdr.nasa.gov/bio).

FAIR↗

Global Analysis of Salmonella Alternative Sigma Factor E on Protein Translation

The alternative sigma factor E (σ E ) is critical for response to extracytoplasmic stress in Salmonella. Extensive studies have been conducted on σ E -regulated gene expression, particularly at the transcriptional level. Increasing evidence suggests however that σ E may indirectly participate in post-transcriptional regulation. Here in this study, we conducted sample-matched global proteomic and transcriptomic analyses to determine the level of regulation mediated by σ E in Salmonella. We analysed samples from wild type and isogenic rpoE mutant Salmonella cultivated in three different conditions; nutrient-rich and conditions that mimic early and late intracellular infection. We found that 30% of the observed proteome was regulated by σ E combining all three conditions. In different growth conditions, σ E affected the expression of a broad spectrum of Salmonella proteins required for miscellaneous functions. Those involved in transport and binding, protein synthesis, and stress response were particularly highlighted. By comparing transcriptomic and proteomic data, we identified genes post-transcriptionally regulated by σ E and found that post-transcriptional regulation was responsible for a majority of changes observed in the σ E -regulated proteome. Further, comparison of transcriptomic and proteomic data from hfq mutant of Salmonella demonstrated that σ E –mediated post-transcriptional regulation was partially dependent on the RNA-binding protein Hfq.

59 BASIC BIOLOGICAL SCIENCES↗

Molecular response of poplar to single and combined ozone and drought

High concentration in ground-level ozone (O 3 ) and water deficit affect forest ecosystems service. Earlier we found intercellular CO 2 concentration and isoprene emission were affected by the combination of O 3 and drought, but the molecular mechanisms controlling these phenotypes are still open questions. In this study, we examined the stomatal conductance (g s ) and transcriptome changes in an O 3 -sensitive hybrid poplar exposed to two O 3 levels [charcoal-filtered ambient air (CF) and non-filtered ambient air plus 40 ppb (NF40)] and two water conditions [well-watered (W) and moderate drought (D)]. NF40 reduced the g s more under D than W. We identified the differentially expressed genes (DEGs) from pairwise comparisons and found the poplar's molecular response to drought was counteracted by elevated O 3 . From nine clusters obtained through K-means clustering, 12 core transcription factors were identified. DEGs involved in isoprene biosynthesis and phytohormones signal pathways indicate the molecular response and stomatal closure of poplar under O 3 and/or drought might be through MEP/DOXP and ABA-dependent pathways. In addition, 102 Helitrons capturing DEGs were involved in response to O 3 and/or drought and related with ABA-dependent pathway. This integrated analysis provides multi-dimensional insights to understand the molecular response to the combination of O 3 and drought.

59 BASIC BIOLOGICAL SCIENCES↗

A Novel G-Protein-Coupled Receptors Gene from Upland Cotton Enhances Salt Stress Tolerance in Transgenic Arabidopsis

Plants have developed a number of survival strategies which are significant for enhancing their adaptation to various biotic and abiotic stress factors. At the transcriptome level, G-protein-coupled receptors (GPCRs) are of great significance, enabling the plants to detect a wide range of endogenous and exogenous signals which are employed by the plants in regulating various responses in development and adaptation. In this research work, we carried out genome-wide analysis of target of Myb1 ( TOM1 ), a member of the GPCR gene family. The functional role of TOM1 in salt stress tolerance was studied using a transgenic Arabidopsis plants over-expressing the gene. By the use of the functional domain PF06454, we obtained 16 TOM genes members in Gossypium hirsutum , 9 in Gossypium arboreum , and 11 in Gossypium raimondii . The genes had varying physiochemical properties, and it is significant to note that all the grand average of hydropathy (GRAVY) values were less than one, indicating that all are hydrophobic in nature. In all the genes analysed here, both the exonic and intronic regions were found. The expression level of Gh_A07G0747 (GhTOM) was significantly high in the transgenic lines as compared to the wild type; a similar trend in expression was observed in all the salt-related genes tested in this study. The study in epidermal cells confirmed the localization of the protein coded by the gene TOM1 in the plasma membrane. Analysis of anti-oxidant enzymes showed higher concentrations of antioxidants in transgenic lines and relatively lower levels of oxidant substances such as H 2 O 2 . The low malondialdehyde (MDA) level in transgenic lines indicated that the transgenic lines had relatively low level of oxidative damage compared to the wild types. The results obtained indicate that Gh_A07G0747 (GhTOM) can be a putative target gene for enhancing salt stress tolerance in plants and could be exploited in the future for the development of salt stress-tolerant cotton cultivars.

G-protein-coupled receptors↗

Genome Sequencing and Comparative Analysis of the Biocontrol Agent Trichoderma harzianum sensu stricto TR274

Biological control is a complex process which requires many mechanisms and a high diversity of biochemical pathways. The species of Trichoderma harzianum are well known for their biocontrol activity against many plant pathogens. To gain new insights into the biocontrol mechanism used by T. harzianum, we sequenced the isolate TR274 genome using Illumina. The assembly was performed using AllPaths-LG with a maximum coverage of 100x. The assembly resulted in 2282 contigs with a N50 of 37033bp. The genome size generated was 40.8 Mb and the GC content was 47.7%, similar to other Trichoderma genomes. Using the JGI Annotation Pipeline we predicted 13,932 genes with a high transcriptome support. CEGMA tests suggested 100% genome completeness and 97.9% of RNA-SEQ reads were mapped to the genome. The phylogenetic comparison using orthologous proteins with all Trichoderma genomes sequenced at JGI, corroborates the Trichoderma (T. asperellum and T. atroviride), Longibrachiatum (T. reesei and T. longibrachiatum) and Pachibasium (T. harzianum and T. virens) section division described previously. The comparison between two Trichoderma harzianum species suggests a high genome similarity but some strain-specific expansions. Analyses of the secondary metabolites, CAZymes, transporters, proteases, transcription factors were performed. The Pachybasium section expanded virtually all categories analyzed compared with the other sections, specially Longibrachiatum section, that shows a clear contraction. These results suggests that these proteins families have an important role in their respective phenotypes. Future analysis will improve the understanding of this complex genus and give some insights about its lifestyle and the interactions with the environment.

Steindorff, Andrei S.↗