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At least 739 records · Page 41

All sources NASA NTRS DOE OSTI

DOE OSTI2016

Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction

Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies. Molecular & Cellular Proteomics 16: 10.1074/mcp.M116.060301, 121–134, 2017.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

A Gene Expression and Histologic Approach to Study Production and Outflow of Cerebrospinal Fluid in Hindlimb Suspended Rats

INTRODUCTION: The Spaceflight Associated Neuro-ocular Syndrome (SANS) is thought to be associated with weightlessness-induced cephalad fluid shift, possibly associated with a chronic elevation of intracranial pressure (ICP) during long-duration ISS missions. Changes in cerebrospinal fluid (CSF) dynamics and cranial compliance might be involved in the ICP increase. It is not known whether CSF production and/or outflow are altered in microgravity, but changes at the molecular and cellular level in the structures that produce and regulate the transcellular and paracellular secretion and reabsorption of CSF may be relevant. In this study, we used the rat hindlimb suspension (HS) model to examine the relationship between intracranial pressure (ICP) and the cellular responses to the prolonged change in body posture elicited specifically in the choroid plexus (CP). This was evaluated by transcriptomics, histopathology and ultrastructure of the CP and arachnoid villi (AV). METHODS: ICP was measured by telemetry. The morphology, ultrastructure, and gene expression profile of the CP was examined using male 9-month-old Long Evans rats subjected to HS for 14 and 90 days. A subset of animals completing 90-day HS returned to normal posture for 14 and 90 additional days of recovery. All HS rats had age-matched cage controls maintained in normal posture. A group of animals was maintained in conditions of 1% CO2 throughout the entire protocol. The rat brains were carefully removed and preserved for various analyses, including transmission electron microscopy (TEM), immunohistochemical analysis of specific targets involved in CSF regulation, and RNA sequencing analysis of laser capture micro-dissected CP tissue from the lateral ventricles. SUMMARY OF RESULTS: The ICP record was limited, which impacted any conclusions derived from the results. However, the ICP of rats in the CO2-enriched atmosphere appeared increased compared to those in a normal air composition. HS of rats resulted in an altered transcriptomics profile in the choroid plexus compared to animals maintained at normal posture. This was observed during both the HS period and during normal posture recovery period following 90 days of suspension. The greatest number of differentially expressed genes was observed at 90 days HS. Elevated CO2 also led to a different transcriptomics profile in the CP. The histology and ultrastructure results should be considered preliminary due to the limited number of samples. Examination of the CP by TEM showed blood vessel congestion and microvilli swelling in the CP, as well as some subpial and periventricular gliosis, but no associations were observed with treatment. There was no evidence of a reduced clearance of b-amyloid in the periventricular, perivascular and subpial regions of the brain in HS animals versus those in normal posture. Immunohistochemical staining of aquaporin 4, showed the localization to the subpial region and ependyma with increased immunoreactivity in the brains of CO2 exposed rats. This work was supported by awards NNX15AW48G to S.Z. Animal tissue and live data was provided under a tissue/data sharing agreement with Dr. Charles Fuller, UC Davis.

S B Zanello↗

NASA NTRSDate not supplied

A Gene Expression and Histologic Approach to Study Production and Outflow of Cerebrospinal Fluid in Hindlimb Suspended RATS

S B Zanello↗

DOE OSTI2015

Differential DNA methylation profile of key genes in malignant prostate epithelial cells transformed by inorganic arsenic or cadmium

Previous work shows altered methylation patterns in inorganic arsenic (iAs)- or cadmium (Cd)-transformed epithelial cells. Here, the methylation status near the transcriptional start site was assessed in the normal human prostate epithelial cell line (RWPE-1) that was malignantly transformed by 10 μM Cd for 11 weeks (CTPE) or 5 μM iAs for 29 weeks (CAsE-PE), at which time cells showed multiple markers of acquired cancer phenotype. Next generation sequencing of the transcriptome of CAsE-PE cells identified multiple dysregulated genes. Of the most highly dysregulated genes, five genes that can be relevant to the carcinogenic process (S100P, HYAL1, NTM, NES, ALDH1A1) were chosen for an in-depth analysis of the DNA methylation profile. DNA was isolated, bisulfite converted, and combined bisulfite restriction analysis was used to identify differentially methylated CpG sites, which was confirmed with bisulfite sequencing. Four of the five genes showed differential methylation in transformants relative to control cells that was inversely related to altered gene expression. Increased expression of HYAL1 (> 25-fold) and S100P (> 40-fold) in transformants was correlated with hypomethylation near the transcriptional start site. Decreased expression of NES (> 15-fold) and NTM (> 1000-fold) in transformants was correlated with hypermethylation near the transcriptional start site. ALDH1A1 expression was differentially expressed in transformed cells but was not differentially methylated relative to control. In conclusion, altered gene expression observed in Cd and iAs transformed cells may result from altered DNA methylation status. - Highlights: • Cd and iAs are known human carcinogens, yet neither appears directly mutagenic. • Prior data suggest epigenetic modification plays a role in Cd or iAs induced cancer. • Altered methylation of four misregulated genes was found in Cd or iAs transformants. • The resulting altered gene expression may be relevant to cellular transformation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2012

A systematic comparison of genome-scale clustering algorithms

Background: A wealth of clustering algorithms has been applied to gene co-expression experiments. These algorithms cover a broad range of approaches, from conventional techniques such as k-means and hierarchical clustering, to graphical approaches such as k-clique communities, weighted gene co-expression networks (WGCNA) and paraclique. Comparison of these methods to evaluate their relative effectiveness provides guidance to algorithm selection, development and implementation. Most prior work on comparative clustering evaluation has focused on parametric methods. Graph theoretical methods are recent additions to the tool set for the global analysis and decomposition of microarray co-expression matrices that have not generally been included in earlier methodological comparisons. In the present study, a variety of parametric and graph theoretical clustering algorithms are compared using well-characterized transcriptomic data at a genome scale from Saccharomyces cerevisiae. Methods: For each clustering method under study, a variety of parameters were tested. Jaccard similarity was used to measure each cluster’s agreement with every GO and KEGG annotation set, and the highest Jaccard score was assigned to the cluster. Clusters were grouped into small, medium, and large bins, and the Jaccard score of the top five scoring clusters in each bin were averaged and reported as the best average top 5 (BAT5) score for the particular method. Results: Clusters produced by each method were evaluated based upon the positive match to known pathways. This produces a readily interpretable ranking of the relative effectiveness of clustering on the genes. Methods were also tested to determine whether they were able to identify clusters consistent with those identified by other clustering methods. Conclusions: Validation of clusters against known gene classifications demonstrate that for this data, graph-based techniques outperform conventional clustering approaches, suggesting that further development and application of combinatorial strategies is warranted.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2020

GeneLab

GeneLab collects and enables analysis of spaceflight and ground-based spaceflight simulation genomic data, RNA and protein expression, and metabolic profiles. It interfaces with other existing databases containing spaceflight omic data. The 2011 National Research Council (NRC) Decadal Survey on NASA Life and Physical Sciences called for increased opportunities for multi-investigator spaceflight opportunities and greater use of genomic approaches to meet the needs of NASA researchers. To address these recommendations of the NRC Decadal Survey, the Space Life and Physical Sciences Research and Applications Division of NASA's Human Exploration and Operations Mission Directorate has initiated a transition to an Open Science architecture to increase research opportunities, and has developed the GeneLab Platform based on highly leveraged and integrated bioinformatics analytics. GeneLab is an interactive, open-access resource where scientists can upload, download, store, search, share, transfer, and analyze omics data from spaceflight and corresponding analogue experiments. Users can explore GeneLab datasets in the Data Repository, analyze data using the Analysis Platform, visualize high-order data and create collaborative projects using the Collaborative Workspace. Our primary goal is to maximize the utilization of the valuable biological research conducted aboard the International Space Station (ISS) by collecting genomic, transcriptomic, proteomic, and metabolomics data known as “omics”. By providing a portal linking processed data to flight parameters, GeneLab enables exploration of the molecular network responses of terrestrial biology to the space environment. This allows researchers to understand the complex responses of biological systems to the space environment. This technology development activity was transferred from the Human Exploration and Operations Mission Directorate to the Science Mission Directorate Division of Biological and Physical Sciences (BPS) in October 2020.

GeneLab↗

NASA NTRS2019

GeneLab: A Systems Biology Platform for Omics Analysis

NASA GeneLab is an open-access repository for omics datasets generated by biological experiments conducted in space or experiments relevant to spaceflight (e.g. simulated cosmic radiation, simulated microgravity, bed rest studies). The GeneLab Data Systems (GLDS) version 4.0 will be available on October 1st 2019, and will provide the latest in terms of professional state-of-the-art bioinformatics platform for the space biology and radiation community to upload their data into an omics data commons, to process their data with vetted standard workflows and to compare to existing analyses. Started in 2015 as a repository designed to archive omics data from space experiments, GeneLab has expanded its scope to all ionizing radiation omics experiments conducted on the ground and has put considerable effort in providing carefully characterized radiation metadata on all dataset. GeneLab is also providing processed data derived from the raw data covering a large spectrum of omics (genome, epigenome, transcriptome, epitranscriptome, proteome, metabolome) to help users explore important questions: 1) Which genes or proteins are expressed differently in space for various living organisms? 2) What specific DNA mutations or epigenetic changes happen in space or after exposure to ionizing radiation? and 3) How does genetics affect these responses? Processed data available on GeneLab are derived by standard data analysis workflows vetted by hundreds of scientists who volunteered to join one of the four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG). In this presentation, we will discuss how to bridge the gap between irradiation studies performed on earth and biological experiments conducted in space since the early 1990's. We will discuss how radiation dosimetry was estimated for datasets derived from samples collected during the Space Shuttle era or on the International Space Station. Finally, we will address future strategies regarding dose monitoring in future missions into space, inter-agency efforts to unify data under one umbrella, and knowledge dissemination across the radiation research community and the space biology community.

open-science↗

DOE OSTI2020

Chapter 5: Methods for Algal Protein Isolation and Proteome Analysis

Microalgae present promising feedstocks to produce renewable fuel and chemical intermediates, in part due to high storage carbon flux capacity to triacylglycerides or storage carbohydrates upon nutrient deprivation. However, the mechanism(s) governing deprivation-mediated carbon partitioning remain to be fully elucidated, limiting targeted strain engineering strategies in algal biocatalysts. Though genomic and transcriptomic analyses offer key insights into these mechanisms, active post-transcriptional regulatory mechanisms, ubiquitous in many microalgae, necessitate proteomic and post-translational (e.g., phospho- and nitroso-proteomic) analyses to more completely evaluate algal responsiveness to nutrient deprivation. Herein, we describe methods for isolating total algal protein and conducting proteomic, phosphoproteomic, and nitrosoproteomic analyses. We focus on methods deployed for the chlorophyte, Chlorella vulgaris, a model oleaginous alga with high flux to renewable fuel and chemical precursors.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗

DOE OSTI2016

MAGE-A1 promotes melanoma proliferation and migration through C-JUN activation

MAGE-A1 belongs to the chromosome X-clustered genes of cancer-testis antigen family and is normally expressed in the human germ line but is also overexpressed in various tumors. Previous studies of MAGE-A1 in melanoma mainly focused on methylation changes or its role in immunotherapy, however, its biological functions in melanoma have remained unknown. In order to determine the role of MAGE-A1 in melanoma growth and metastasis, we manipulated melanoma cell lines with overexpression and knockdown of MAGE-A1. Integration of cell proliferation assays, transwell migration and invasion assays, and RNA-Seq analysis revealed that up-regulation of MAGE-A1 dramatically promoted proliferation, migration, and invasion of human melanoma cell lines in vitro, while down-regulation of MAGE-A1 inhibited those characteristics associated with tumor cells. Furthermore, transcriptome sequencing revealed that MAGE-A1 exerts its tumor promoting activity by activating p-C-JUN directly or through ERK-MAPK signaling pathways. Based on our findings, we propose that MAGE-A1 may be a potential therapeutic target for melanoma patients. - Highlights: • MAGE-A1 promotes proliferation and clone formation in melanoma cell lines. • MAGE-A1 enhances tumor cell migration and invasion in melanoma cell lines. • Network including C-JUN, IL8, and ARHGAP29 play critical role in malignant melanoma. • Oncogenic MAGE-A1 increases p-C-JUN levels, possibly via ERK-MAPK signaling pathway.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

A System for Dosage-Based Functional Genomics in Poplar

Altering gene dosage through variation in gene copy number is a powerful approach to addressing questions regarding gene regulation, quantitative trait loci, and heterosis, but one that is not easily applied to sexually transmitted species. Elite poplar (Populus spp) varieties are created through interspecific hybridization, followed by clonal propagation. Altered gene dosage relationships are believed to contribute to hybrid performance. Clonal propagation allows for replication and maintenance of meiotically unstable ploidy or structural variants and provides an alternative approach to investigating gene dosage effects not possible in sexually propagated species. Here, we built a genome-wide structural variation system for dosage-based functional genomics and breeding of poplar. We pollinated Populus deltoides with gamma-irradiated Populus nigra pollen to produce >500 F1 seedlings containing dosage lesions in the form of deletions and insertions of chromosomal segments (indel mutations). Using high-precision dosage analysis, we detected indel mutations in ~55% of the progeny. These indels varied in length, position, and number per individual, cumulatively tiling >99% of the genome, with an average of 10 indels per gene. Combined with future phenotype and transcriptome data, this population will provide an excellent resource for creating and characterizing dosage-based variation in poplar, including the contribution of dosage to quantitative traits and heterosis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

BaRTv1.0: an improved barley reference transcript dataset to determine accurate changes in the barley transcriptome using RNA-seq

A high confidence barley reference transcript dataset consisting of 60,444 genes with 177,240 transcripts has been generated. Compared to current barley transcripts, BaRTv1.0 transcripts are generally longer, have less fragmentation and improved gene models that are well supported by splice junction reads. Precise transcript quantification using BaRTv1.0 allows routine analysis of gene expression and AS.

barley↗

NASA NTRS2016

Genelab: Scientific Partnerships and an Open-Access Database to Maximize Usage of Omics Data from Space Biology Experiments

NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. The GeneLab Data System (GLDS) is NASA's premier open-access omics data platform for biological experiments. GLDS houses standards-compliant, high-throughput sequencing and other omics data from spaceflight-relevant experiments. The GeneLab project at NASA-Ames Research Center is developing the database, and also partnering with spaceflight projects through sharing or augmentation of experiment samples to expand omics analyses on precious spaceflight samples. The partnerships ensure that the maximum amount of data is garnered from spaceflight experiments and made publically available as rapidly as possible via the GLDS. GLDS Version 1.0, went online in April 2015. Software updates and new data releases occur at least quarterly. As of October 2016, the GLDS contains 80 datasets and has search and download capabilities. Version 2.0 is slated for release in September of 2017 and will have expanded, integrated search capabilities leveraging other public omics databases (NCBI GEO, PRIDE, MG-RAST). Future versions in this multi-phase project will provide a collaborative platform for omics data analysis. Data from experiments that explore the biological effects of the spaceflight environment on a wide variety of model organisms are housed in the GLDS including data from rodents, invertebrates, plants and microbes. Human datasets are currently limited to those with anonymized data (e.g., from cultured cell lines). GeneLab ensures prompt release and open access to high-throughput genomics, transcriptomics, proteomics, and metabolomics data from spaceflight and ground-based simulations of microgravity, radiation or other space environment factors. The data are meticulously curated to assure that accurate experimental and sample processing metadata are included with each data set. GLDS download volumes indicate strong interest of the scientific community in these data. To date GeneLab has partnered with multiple experiments including two plant (Arabidopsis thaliana) experiments, two mice experiments, and several microbe experiments. GeneLab optimized protocols in the rodent partnerships for maximum yield of RNA, DNA and protein from tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected on the ground. Analysis of GeneLab data will contribute fundamental knowledge of how the space environment affects biological systems, and as well as yield terrestrial benefits resulting from mitigation strategies to prevent effects observed during exposure to space environments.

bioinformatics↗

NASA NTRS2016

GeneLab: Scientific Partnerships and an Open-Access Database to Maximize Usage of Omics Data from Space Biology Experiments

NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. The GeneLab Data System (GLDS) is NASAs premier open-access omics data platform for biological experiments. GLDS houses standards-compliant, high-throughput sequencing and other omics data from spaceflight-relevant experiments. The GeneLab project at NASA-Ames Research Center is developing the database, and also partnering with spaceflight projects through sharing or augmentation of experiment samples to expand omics analyses on precious spaceflight samples. The partnerships ensure that the maximum amount of data is garnered from spaceflight experiments and made publically available as rapidly as possible via the GLDS. GLDS Version 1.0, went online in April 2015. Software updates and new data releases occur at least quarterly. As of October 2016, the GLDS contains 80 datasets and has search and download capabilities. Version 2.0 is slated for release in September of 2017 and will have expanded, integrated search capabilities leveraging other public omics databases (NCBI GEO, PRIDE, MG-RAST). Future versions in this multi-phase project will provide a collaborative platform for omics data analysis. Data from experiments that explore the biological effects of the spaceflight environment on a wide variety of model organisms are housed in the GLDS including data from rodents, invertebrates, plants and microbes. Human datasets are currently limited to those with anonymized data (e.g., from cultured cell lines). GeneLab ensures prompt release and open access to high-throughput genomics, transcriptomics, proteomics, and metabolomics data from spaceflight and ground-based simulations of microgravity, radiation or other space environment factors. The data are meticulously curated to assure that accurate experimental and sample processing metadata are included with each data set. GLDS download volumes indicate strong interest of the scientific community in these data. To date GeneLab has partnered with multiple experiments including two plant (Arabidopsis thaliana) experiments, two mice experiments, and several microbe experiments. GeneLab optimized protocols in the rodent partnerships for maximum yield of RNA, DNA and protein from tissues harvested and preserved during the SpaceX-4 mission, as well as from tissues from mice that were frozen intact during spaceflight and later dissected on the ground. Analysis of GeneLab data will contribute fundamental knowledge of how the space environment affects biological systems, and as well as yield terrestrial benefits resulting from mitigation strategies to prevent effects observed during exposure to space environments.

spaceflight↗

DOE OSTI2018

Activation of JNK signaling in osteoblasts is inversely correlated with collagen synthesis in age-related osteoporosis

Highlights: • Transcription of five collagen members, e.g., COL12A1 and COL8A2, reduced significantly in the osteoblasts of old donors. • Oxidoreductase activity and kinase activity were inversely correlated with collagen expression in aged osteoblasts. • Gene expression signature of JNK signaling was enriched in aged osteoblasts. • MAP3K4 and MAP4K2 were upregulated and inversely correlated with collagen expression in aged osteoblasts. The age-related reduction in the function of osteoblasts plays a central role in the pathogenesis of bone loss and osteoporosis. Collagen synthesis is a primary function of differentiated osteoblasts, however, the mechanisms for age-related changes in collagen synthesis in human osteoblasts remain elusive. We use Gene Ontology (GO) analysis and Gene Set Enrichment Analysis (GSEA) analysis to exploit the transcriptional profiles of osteoblasts from young and old donors. A panel of collagen members was downregulated in aged osteoblasts, including COL12A1, COL5A1, COL5A3, COL8A1 and COL8A2. Co-expression analysis followed by GO analysis revealed that oxidoreductase activity and kinase activity were inversely correlated with collagen synthesis in osteoblasts. GESA analysis further showed that JNK signaling was upregulated in aged osteoblasts. Consistently, MAP3K4 and MAP4K2, upstream of JNK, were also increased in aged osteoblasts. Moreover, expression levels of MAP3K4 were significantly inversely correlated with levels of the collagen genes. Those transcriptomic results were further verified by examining clinical specimens of osteoporosis by immunohistochemistry. These results provide transcriptomic evidence that deregulated JNK signaling may impair collagen synthesis in osteoblasts and imply a therapeutic value of JNK inhibitors for treating osteoporosis and preventing skeletal aging by counteracting the age-related reduction in the function of osteoblasts.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

Multi-omic data integration links Deleted in Breast Cancer 1 (DBC1) Degradation to Chromatin Remodeling in Inflammatory Response

Ubiquitination is a common protein post-translational modification that regulates many key cellular functions. Here we investigated the dynamics of ubiquitinated proteins after an inflammatory stimulation of RAW264.7 macrophage-like cells with bacterial lipopolysaccharide. We demonstrate that levels of global ubiquitination, and K48 and K63 polyubiquitination change after lipopolysaccharide stimulation. A quantitative proteomic analysis identified 1199 ubiquitinated proteins, 78 of which had significantly changed ubiquitination levels after lipopolysaccharide stimulation. We next identified a subset of proteins that were targeted for degradation after lipopolysaccharide stimulation, by integrating the ubiquitinome data with global proteomics and transcriptomics results. Using cellular assays and western blot analyses we biochemically validated DBC1, a histone deacetylase inhibitor not previously linked to inflammation, as a degradation substrate, which is targeted via an orchestrated mechanism utilizing caspases and the proteasome. The degradation of DBC1 releases histone deacetylase activity, linking lipopolysaccharide activation to chromatin remodeling in caspase- and proteasome-mediated signaling.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2013

Systems biology analysis of Zymomonas mobilis ZM4 ethanol stress responses

Zymomonas mobilis ZM4 is a capable ethanogenic bacterium with high ethanol productivity and high level of ethanol tolerance. Previous studies indicated that several stress-related proteins and changes in the ZM4 membrane lipid composition may contribute to ethanol tolerance. However, the molecular mechanisms of ethanol stress response have not been elucidated fully. In this study, ethanol stress responses were investigated using systems biology tools. Medium supplementation with an initial 47.3 g/L (6% v/v) ethanol reduced Z. mobilis ZM4 glucose consumption, growth rate and ethanol productivity compared to that of untreated controls. Metabolomic profiling showed that ethanol-treated ZM4 cells accumulated greater amounts of glycerol during the entire fermentation process, which may indicate an important role for this metabolite. A proteomic analysis of early exponential growth identified about one thousand proteins, or approximately 56% of the predicted ZM4 proteome. Proteins related to metabolism and stress response such as chaperones and key regulators were more abundant in the early ethanol stress condition. Transcriptomic studies indicated the response of ZM4 to ethanol is dynamic, complex and involves many genes from all the different functional categories. There were fewer genes significantly differentially expressed in the exponential phase compared to that of stationary phase and early stationary phase. Most down-regulated genes were related to translation and ribosome biogenesis, while the ethanol-upregulated genes were mostly related to cellular processes and metabolism. Correlations among the transcriptomics, proteomics and metabolism were examined and among significantly expressed genes or proteins, we observe higher correlation coefficients when fold-change values are higher. This systems biology study elucidates key Z. mobilis ZM4 metabolites, genes and proteins that form the foundation of its distinctive physiology and its multifaceted response to ethanol stress.

BESC LDRD↗

DOE OSTI2026

Comparison of gene expression in the skin tissue of gray, humpback, and fin whales

Analyses of gene expression in the skin of several species of whales identified genes that are differentially expressed in association with environmental factors, suggesting that skin transcriptomics may provide a valuable tool for assessing physiological responses in marine mammals. Previous work exploring differing levels of gene expression has focused on odontocetes with comparatively limited investigation of skin gene expression has been explored in mysticetes. Here, we describe the identity of genes expressed in skin tissue of three species of baleen whales to establish a baseline of gene expression and compare gene identity and expression patterns across species. We also evaluate sex-specific differences in skin gene expression through a comparison of expression levels between males and females in gray and humpback whales. A total of 16 skin tissue samples were collected from free-ranging gray, humpback and fin whales off the central Oregon coast in the eastern North Pacific. Comparison of the expressed genes in the humpback and gray whale skin tissue to the blue whale reference database identified enriched gene ontology terms in the skin tissue of each species, suggesting genes over-represented in the whale skin related to cell epithelial development, regulation of gene expression and cell maintenance . Comparison of gene expression between male and female samples revealed sex-specific differences in gray and humpback whales. A differential gene expression analysis identified several x-linked genes that have been previously identified and show gene expression differences in male and female cetaceans, such as ZFX, DDX3X and USP9X. Establishing baseline skin gene expression profiles for these three baleen whale species sampled off the Oregon coast provides a foundation for linking transcriptome variation with physiological condition and environment.

Sremba, Angela↗

DOE OSTI2024

Entire expressed peripheral blood transcriptome in pediatric severe malarial anemia

Abstract This study on severe malarial anemia (SMA: Hb < 6.0 g/dL), a leading global cause of childhood morbidity and mortality, compares the entire expressed whole blood host transcriptome between Kenyan children (3-48 mos.) with non-SMA (Hb ≥ 6.0 g/dL, n = 39) and SMA ( n = 18). Differential expression analyses reveal 1403 up-regulated and 279 down-regulated transcripts in SMA, signifying impairments in host inflammasome activation, cell death, and innate immune and cellular stress responses. Immune cell profiling shows decreased memory responses, antigen presentation, and immediate pathogen clearance, suggesting an immature/improperly regulated immune response in SMA. Module repertoire analysis of blood-specific gene signatures identifies up-regulation of erythroid genes, enhanced neutrophil activation, and impaired inflammatory responses in SMA. Enrichment analyses converge on disruptions in cellular homeostasis and regulatory pathways for the ubiquitin-proteasome system, autophagy, and heme metabolism. Pathway analyses highlight activation in response to hypoxic conditions [Hypoxia Inducible Factor (HIF)−1 target and Reactive Oxygen Species (ROS) signaling] as a central theme in SMA. These signaling pathways are also top-ranking in protein abundance measures and a Ugandan SMA cohort with available transcriptomic data. Targeted RNA-Seq validation shows strong concordance with our entire expressed transcriptome data. These findings identify key molecular themes in SMA pathogenesis, offering potential targets for new malaria therapies.

60 APPLIED LIFE SCIENCES↗