Weighted set enrichment of gene expression data

Transcriptomic Insights into Abies koreana Drought Tolerance Conferred by Aureobasidium pullulans AK10

The conservation of the endangered Korean fir, Abies koreana, is of critical ecological importance. In our previous study, a yeast-like fungus identified as Aureobasidium pullulans AK10, was isolated and shown to enhance drought tolerance in A. koreana seedlings. In this study, the effectiveness of Au. pullulans AK10 treatment in enhancing drought tolerance in A. koreana was confirmed. Furthermore, using transcriptome analysis, we compared A. koreana seedlings treated with Au. pullulans AK10 to untreated controls under drought conditions to elucidate the molecular responses involved in increased drought tolerance. Our findings revealed a predominance of downregulated genes in the treated seedlings, suggesting a strategic reallocation of resources to enhance stress defense. Further exploration of enriched Kyoto Encyclopedia of Genes and Genomes pathways and protein-protein interaction networks revealed significant alterations in functional systems known to fortify drought tolerance, including the terpenoid backbone biosynthesis, calcium signaling pathway, pyruvate metabolism, brassinosteroid biosynthesis, and, crucially, flavonoid biosynthesis, renowned for enhancing plant drought resistance. These findings deepen our comprehension of how AK10 biostimulation enhances the resilience of A. koreana to drought stress, marking a substantial advancement in the effort to conserve this endangered tree species through environmentally sustainable treatment.

Heterospecific Neighbor Plants Impact Root Microbiome Diversity and Molecular Function of Root Fungi

Within the forest community, competition and facilitation between adjacent-growing conspecific and heterospecific plants are mediated by interactions involving common mycorrhizal networks. The ability of plants to alter their neighbor's microbiome is well documented, but the molecular biology of plant-fungal interactions during competition and facilitation has not been previously examined. We used a common soil-plant bioassay experiment to study molecular plant-microbial interactions among rhizosphere communities associated with Pinus taeda (native host) and Populus trichocarpa (non-native host). Gene expression of interacting fungal and bacterial rhizosphere communities was compared among three plant-pairs: Populus growing with Populus, Populus with Pinus, and Pinus with Pinus. Our results demonstrate that heterospecific plant partners affect the assembly of root microbiomes, including the changes in the structure of host specific community. Comparative metatranscriptomics reveals that several species of ectomycorrhizal fungi (EMF) and saprotrophic fungi exhibit different patterns of functional and regulatory gene expression with these two plant hosts. Heterospecific plants affect the transcriptional expression pattern of EMF host-specialists (e.g., Pinus-associated Suillus spp.) on both plant species, mainly including the genes involved in the transportation of amino acids, carbohydrates, and inorganic ions. Alteration of root microbiome by neighboring plants may help regulate basic plant physiological processes via modulation of molecular functions in the root microbiome.

Toward comprehensive functional analysis of gene lists weighted by gene essentiality scores

MOTIVATION

Gene functional enrichment analysis represents one of the most popular bioinformatics methods for annotating the pathways and function categories of a given gene list. Current algorithms for enrichment computation such as Fisher's exact test and hypergeometric test totally depend on the category count numbers of the gene list and one gene set. In this case, whatever the genes are, they were treated equally. However, actually genes show different scores in their essentiality in a gene list and in a gene set. It is thus hypothesized that the essentiality scores could be important and should be considered in gene functional analysis.

RESULTS

For this purpose, here we proposed WEAT (https://www.cuilab.cn/weat/), a weighted gene set enrichment algorithm and online tool by weighting genes using essentiality scores. We confirmed the usefulness of WEAT using three case studies, the functional analysis of one aging-related gene list, one gene list involved in Lung Squamous Cell Carcinoma (LUSC), and one cardiomyopathy gene list from Drosophila model. Finally, we believe that the WEAT method and tool could provide more possibilities for further exploring the functions of given gene lists.

AVAILABILITY

The datasets generated and analyzed during the current study are available on our website at https://www.cuilab.cn/weat/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Pan-Genome Analysis Reveals Host-Specific Functional Divergences in Burkholderia gladioli

Burkholderia gladioli has high versatility and adaptability to various ecological niches. Here, we constructed a pan-genome using 14 genome sequences of B. gladioli, which originate from different niches, including gladiolus, rice, humans, and nature. Functional roles of core and niche-associated genomes were investigated by pathway enrichment analyses. Consequently, we inferred the uniquely important role of niche-associated genomes in (1) selenium availability during competition with gladiolus host; (2) aromatic compound degradation in seed-borne and crude oil-accumulated environments, and (3) stress-induced DNA repair system/recombination in the cystic fibrosis-niche. We also identified the conservation of the rhizomide biosynthetic gene cluster in all the B. gladioli strains and the concentrated distribution of this cluster in human isolates. It was confirmed the absence of complete CRISPR/Cas system in both plant and human pathogenic B. gladioli and the presence of the system in B. gladioli living in nature, possibly reflecting the inverse relationship between CRISPR/Cas system and virulence.

A Pathway Analysis Approach Using Petri Net

Perturbation in the normal function of the cell signaling pathways often leads to diseases. One of the factors that help understand the mechanism of diseases is the precise identification and investigation of perturbed signaling pathways. Pathway analysis methods have been developed as their purpose is to identify perturbed signaling pathways in given conditions. Among these methods, some consider the pathways topologies in their analysis, which are referred to as topology-based methods. Most of the topology-based methods used simple graph-based models to incorporate topology in their analysis, which have some limitations. We describe a new Pathway Analysis method using Petri net (PAPet) that uses the Petri net to model the signaling pathways and then propose an algorithm to measure the perturbation on a given pathway under a given condition. Modeling with Petri net has some advantages and could overcome the shortcomings of the simple graph-based models. We illustrate the capabilities of the proposed method using sensitivity, prioritization, mean reciprocal rank, and false-positive rate metrics on 36 real datasets from various diseases. The results of comparing PAPet with five pathway analysis methods FoPA, PADOG, GSEA, CePa and SPIA show that PAPet is the best one that provides a good compromise between all metrics. In addition, the results of applying methods to gene expression profiles in normal and Pancreatic Ductal Adenocarcinoma cancer (PDAC) samples show that the PAPet method achieves the best rank among others in finding the pathways that have been previously reported for PDAC. The PAPet method is available at https://github.com/fmansoori/PAPET.

DNA adenine methylation is involved in persister formation in E. coli

Uropathogenic Escherichia coli (UPEC) is a major cause of urinary tract infections (UTI). UPEC persister bacteria play crucial roles in clinical treatment failure and relapse. Although DNA methylation is known to regulate gene expression, its role in persister formation has not been investigated. Here, we show that Δdam (adenine methylase) mutant from UPEC strain UTI89 had significant defect in persister formation and complementation of the Δdam mutant restored this defect. Using PacBio sequencing of methylome and RNA sequencing of Δdam, we defined, for the first time, the role of Dam in persister formation. We found that Δdam mutation had an overwhelming effect on demethylation of the genome and the demethylation sites affected expression of genes involved in broad transcriptional and metabolic processes. Using comparative COG analysis of methylome and transcriptome, we demonstrate that Dam mediates persister formation through transcriptional control, cell motility, DNA repair and metabolite transport processes. These findings provide the first evidence and molecular basis for DNA methylation mediated persister formation and implicate Dam DNA methylation as a potential drug target for persister bacteria.

The Developmental Transcriptome of Bagworm, Metisa plana (Lepidoptera: Psychidae) and Insights into Chitin Biosynthesis Genes

Bagworm, Metisa plana (Lepidoptera: Psychidae) is a ubiquitous insect pest in the oil palm plantations. M. plana infestation could reduce the oil palm productivity by 40% if it remains untreated over two consecutive years. Despite the urgency to tackle this issue, the genome and transcriptome of M. plana have not yet been fully elucidated. Here, we report a comprehensive transcriptome dataset from four different developmental stages of M. plana, comprising of egg, third instar larva, pupa and female adult. The de novo transcriptome assembly of the raw data had produced a total of 193,686 transcripts, which were then annotated against UniProt, NCBI non-redundant (NR) database, Gene Ontology, Cluster of Orthologous Group, and Kyoto Encyclopedia of Genes and Genomes databases. From this, 46,534 transcripts were annotated and mapped to 146 known metabolic or signalling KEGG pathways. The paper further identified 41 differentially expressed transcripts encoding seven genes in the chitin biosynthesis pathways, and their expressions across each developmental stage were further analysed. The genetic diversity of M. plana was profiled whereby there were 21,516 microsatellite sequences and 379,895 SNPs loci found in the transcriptome of M. plana. These datasets add valuable transcriptomic resources for further study of developmental gene expression, transcriptional regulations and functional gene activities involved in the development of M. plana. Identification of regulatory genes in the chitin biosynthesis pathway may also help in developing an RNAi-mediated pest control management by targeting certain pathways, and functional studies of the genes in M. plana.

Comparative Transcriptome Analysis of Pine Trees Treated with Resistance-Inducing Substances against the Nematode Bursaphelenchus xylophilus

The pinewood nematode (PWN) Bursaphelenchus xylophilus causes pine wilt disease, which results in substantial economic and environmental losses across pine forests worldwide. Although systemic acquired resistance (SAR) is effective in controlling PWN, the detailed mechanisms underlying the resistance to PWN are unclear. Here, we treated pine samples with two SAR elicitors, acibenzolar-S-methyl (ASM) and methyl salicylic acid (MeSA) and constructed an in vivo transcriptome of PWN-infected pines under SAR conditions. A total of 252 million clean reads were obtained and mapped onto the reference genome. Compared with untreated pines, 1091 and 1139 genes were differentially upregulated following the ASM and MeSA treatments, respectively. Among these, 650 genes showed co-expression patterns in response to both SAR elicitors. Analysis of these patterns indicated a functional linkage among photorespiration, peroxisome, and glycine metabolism, which may play a protective role against PWN infection-induced oxidative stress. Further, the biosynthesis of flavonoids, known to directly control parasitic nematodes, was commonly upregulated under SAR conditions. The ASM- and MeSA-specific expression patterns revealed functional branches for myricetin and quercetin production in flavonol biosynthesis. This study will enhance the understanding of the dynamic interactions between pine hosts and PWN under SAR conditions.

Profiling of glucose-induced transcription in Sulfolobus acidocaldarius DSM 639

Sulfolobus species can grow on a variety of organic compounds as carbon and energy sources. These species degrade glucose to pyruvate by the modified branched Entner-Doudoroff pathway. We attempted to determine the differentially expressed genes (DEGs) under sugar-limited and sugar-rich conditions. RNA sequencing (RNA-seq) was used to quantify the expression of the genes and identify those DEGs between the S. acidocaldarius cells grown under sugar-rich (YT with glucose) and sugar-limited (YT only) conditions. The functions and pathways of the DEGs were examined using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Quantitative real-time PCR (qRT-PCR) was performed to validate the DEGs. Transcriptome analysis of the DSM 639 strain grown on sugar-limited and sugar-rich media revealed that 853 genes were differentially expressed, among which 481 were upregulated and 372 were downregulated under the glucose-supplemented condition. In particular, 70 genes showed significant changes in expression levels of ≥ twofold. GO and KEGG enrichment analyses revealed that the genes encoding components of central carbon metabolism, the respiratory chain, and protein and amino acid biosynthetic machinery were upregulated under the glucose condition. RNA-seq and qRT-PCR analyses indicated that the sulfur assimilation genes (Saci_2197-2204) including phosphoadenosine phosphosulfate reductase and sulfite reductase were significantly upregulated in the presence of glucose. The present study revealed metabolic networks in S. acidocaldarius that are induced in a glucose-dependent manner, improving our understanding of biomass production under sugar-rich conditions.

Transcriptional Profile of Mycobacterium tuberculosis in an in vitro Model of Intraocular Tuberculosis

Background: Intraocular tuberculosis (IOTB), an extrapulmonary manifestation of tuberculosis of the eye, has unique and varied clinical presentations with poorly understood pathogenesis. As it is a significant cause of inflammation and visual morbidity, particularly in TB endemic countries, it is essential to study the pathogenesis of IOTB. Clinical and histopathologic studies suggest the presence of Mycobacterium tuberculosis in retinal pigment epithelium (RPE) cells. Methods: A human retinal pigment epithelium (ARPE-19) cell line was infected with a virulent strain of M. tuberculosis (H37Rv). Electron microscopy and colony forming units (CFU) assay were performed to monitor the M. tuberculosis adherence, invasion, and intracellular replication, whereas confocal microscopy was done to study its intracellular fate in the RPE cells. To understand the pathogenesis, the transcriptional profile of M. tuberculosis in ARPE-19 cells was studied by whole genome microarray. Three upregulated M. tuberculosis transcripts were also examined in human IOTB vitreous samples. Results: Scanning electron micrographs of the infected ARPE-19 cells indicated adherence of bacilli, which were further observed to be internalized as monitored by transmission electron microscopy. The CFU assay showed that 22.7 and 8.4% of the initial inoculum of bacilli adhered and invaded the ARPE-19 cells, respectively, with an increase in fold CFU from 1 dpi (0.84) to 5dpi (6.58). The intracellular bacilli were co-localized with lysosomal-associated membrane protein-1 (LAMP-1) and LAMP-2 in ARPE-19 cells. The transcriptome study of intracellular bacilli showed that most of the upregulated transcripts correspond to the genes encoding the proteins involved in the processes such as adherence (e.g., Rv1759c and Rv1026), invasion (e.g., Rv1971 and Rv0169), virulence (e.g., Rv2844 and Rv0775), and intracellular survival (e.g., Rv1884c and Rv2450c) as well as regulators of various metabolic pathways. Two of the upregulated transcripts (Rv1971, Rv1230c) were also present in the vitreous samples of the IOTB patients. Conclusions:M. tuberculosis is phagocytosed by RPE cells and utilizes these cells for intracellular multiplication with the involvement of late endosomal/lysosomal compartments and alters its transcriptional profile plausibly for its intracellular adaptation and survival. The findings of the present study could be important to understanding the molecular pathogenesis of IOTB with a potential role in the development of diagnostics and therapeutics for IOTB.

Cooperative interactions between seed-borne bacterial and air-borne fungal pathogens on rice

Bacterial-fungal interactions are widely found in distinct environments and contribute to ecosystem processes. Previous studies of these interactions have mostly been performed in soil, and only limited studies of aerial plant tissues have been conducted. Here we show that a seed-borne plant pathogenic bacterium, Burkholderia glumae (Bg), and an air-borne plant pathogenic fungus, Fusarium graminearum (Fg), interact to promote bacterial survival, bacterial and fungal dispersal, and disease progression on rice plants, despite the production of antifungal toxoflavin by Bg. We perform assays of toxoflavin sensitivity, RNA-seq analyses, lipid staining and measures of triacylglyceride content to show that triacylglycerides containing linolenic acid mediate resistance to reactive oxygen species that are generated in response to toxoflavin in Fg. As a result, Bg is able to physically attach to Fg to achieve rapid and expansive dispersal to enhance disease severity.

A Role for Timp3 in Microbiota-Driven Hepatic Steatosis and Metabolic Dysfunction

The effect of gut microbiota on obesity and insulin resistance is now recognized, but the underlying host-dependent mechanisms remain poorly undefined. We find that tissue inhibitor of metalloproteinase 3 knockout (Timp3(-/-)) mice fed a high-fat diet exhibit gut microbiota dysbiosis, an increase in branched chain and aromatic (BCAA) metabolites, liver steatosis, and an increase in circulating soluble IL-6 receptors (sIL6Rs). sIL6Rs can then activate inflammatory cells, such as CD11c(+) cells, which drive metabolic inflammation. Depleting the microbiota through antibiotic treatment significantly improves glucose tolerance, hepatic steatosis, and systemic inflammation, and neutralizing sIL6R signaling reduces inflammation, but only mildly impacts glucose tolerance. Collectively, our results suggest that gut microbiota is the primary driver of the observed metabolic dysfunction, which is mediated, in part, through IL-6 signaling. Our findings also identify an important role for Timp3 in mediating the effect of the microbiota in metabolic diseases.

MicroRNA Expression Profiling in CCl₄-Induced Liver Fibrosis of Mus musculus

Liver fibrosis is a major pathological feature of chronic liver diseases, including liver cancer. MicroRNAs (miRNAs), small noncoding RNAs, regulate gene expression posttranscriptionally and play important roles in various kinds of diseases; however, miRNA-associated hepatic fibrogenesis and its acting mechanisms are poorly investigated. Therefore, we performed an miRNA microarray in the fibrotic livers of Mus musculus treated with carbon-tetrachloride (CCl₄) and analyzed the biological functions engaged by the target genes of differentially-expressed miRNAs through gene ontology (GO) and in-depth pathway enrichment analysis. Herein, we found that four miRNAs were upregulated and four miRNAs were downregulated more than two-fold in CCl₄-treated livers compared to a control liver. Eight miRNAs were predicted to target a total of 4079 genes. GO analysis revealed that those target genes were located in various cellular compartments, including cytoplasm, nucleolus and cell surface, and they were involved in protein-protein or protein-DNA bindings, which influence the signal transductions and gene transcription. Furthermore, pathway enrichment analysis demonstrated that the 72 subspecialized signaling pathways were associated with CCl₄-induced liver fibrosis and were mostly classified into metabolic function-related pathways. These results suggest that CCl₄ induces liver fibrosis by disrupting the metabolic pathways. In conclusion, we presented several miRNAs and their biological processes that might be important in the progression of liver fibrosis; these findings help increase the understanding of liver fibrogenesis and provide novel ideas for further studies of the role of miRNAs in liver fibrosis.

Pathway Analysis: State of the Art

Pathway analysis is a set of widely used tools for research in life sciences intended to give meaning to high-throughput biological data. The methodology of these tools settles in the gathering and usage of knowledge that comprise biomolecular functioning, coupled with statistical testing and other algorithms. Despite their wide employment, pathway analysis foundations and overall background may not be fully understood, leading to misinterpretation of analysis results. This review attempts to comprise the fundamental knowledge to take into consideration when using pathway analysis as a hypothesis generation tool. We discuss the key elements that are part of these methodologies, their capabilities and current deficiencies. We also present an overview of current and all-time popular methods, highlighting different classes across them. In doing so, we show the exploding diversity of methods that pathway analysis encompasses, point out commonly overlooked caveats, and direct attention to a potential new class of methods that attempt to zoom the analysis scope to the sample scale.

Integrative enrichment analysis: a new computational method to detect dysregulated pathways in heterogeneous samples

BACKGROUND

Pathway enrichment analysis is a useful tool to study biology and biomedicine, due to its functional screening on well-defined biological procedures rather than separate molecules. The measurement of malfunctions of pathways with a phenotype change, e.g., from normal to diseased, is the key issue when applying enrichment analysis on a pathway. The differentially expressed genes (DEGs) are widely focused in conventional analysis, which is based on the great purity of samples. However, the disease samples are usually heterogeneous, so that, the genes with great differential expression variance (DEVGs) are becoming attractive and important to indicate the specific state of a biological system. In the context of differential expression variance, it is still a challenge to measure the enrichment or status of a pathway. To address this issue, we proposed Integrative Enrichment Analysis (IEA) based on a novel enrichment measurement.

RESULTS

The main competitive ability of IEA is to identify dysregulated pathways containing DEGs and DEVGs simultaneously, which are usually under-scored by other methods. Next, IEA provides two additional assistant approaches to investigate such dysregulated pathways. One is to infer the association among identified dysregulated pathways and expected target pathways by estimating pathway crosstalks. The other one is to recognize subtype-factors as dysregulated pathways associated to particular clinical indices according to the DEVGs' relative expressions rather than conventional raw expressions. Based on a previously established evaluation scheme, we found that, in particular cohorts (i.e., a group of real gene expression datasets from human patients), a few target disease pathways can be significantly high-ranked by IEA, which is more effective than other state-of-the-art methods. Furthermore, we present a proof-of-concept study on Diabetes to indicate: IEA rather than conventional ORA or GSEA can capture the under-estimated dysregulated pathways full of DEVGs and DEGs; these newly identified pathways could be significantly linked to prior-known disease pathways by estimated crosstalks; and many candidate subtype-factors recognized by IEA also have significant relation with the risk of subtypes of genotype-phenotype associations.

CONCLUSIONS

Totally, IEA supplies a new tool to carry on enrichment analysis in the complicate context of clinical application (i.e., heterogeneity of disease), as a necessary complementary and cooperative approach to conventional ones.

Publisher’s Note:Abstraction for data integration:Fusing mammalian molecular, cellular and phenotype big datasets for better knowledge extraction

With advances in genomics, transcriptomics, metabolomics and proteomics, and more expansive electronic clinical record monitoring, as well as advances in computation, we have entered the Big Data era in biomedical research. Data gathering is growing rapidly while only a small fraction of this data is converted to useful knowledge or reused in future studies. To improve this, an important concept that is often overlooked is data abstraction. To fuse and reuse biomedical datasets from diverse resources, data abstraction is frequently required. Here we summarize some of the major Big Data biomedical research resources for genomics, proteomics and phenotype data, collected from mammalian cells, tissues and organisms. We then suggest simple data abstraction methods for fusing this diverse but related data. Finally, we demonstrate examples of the potential utility of such data integration efforts, while warning about the inherit biases that exist within such data.

Transcriptome analyses to understand effects of the Fusarium deoxynivalenol and nivalenol mycotoxins on Escherichia coli

Fusarium spp. cause many diseases in farming systems and can produce diverse mycotoxins that can easily impact humans and animals through the ingestion of food and feed. Among these mycotoxins, deoxynivalenol (DON) and nivalenol (NIV) are considered the most important hazards because they can rapidly diffuse into cells and block eukaryotic ribosomes, leading to inhibition of the translation system. Conversely, the effects of DON and NIV mycotoxins on bacteria remain unclear. We employed RNA-seq technology to obtain information regarding the biological responses of bacteria and putative bacterial mechanisms of resistance to DON and NIV mycotoxins. Most differentially expressed genes down-regulated in response to these mycotoxins were commonly involved in phenylalanine metabolism, glyoxylate cycle, and cytochrome o ubiquinol oxidase systems. In addition, we generated an overall network of 1028 up-regulated genes to identify core genes under DON and NIV conditions. The results of our study provide a snapshot view of the transcriptome of Escherichia coli K-12 under DON and NIV conditions. Furthermore, the information provided herein will be useful for development of methods to detect DON and NIV.

Understanding pathogenic Burkholderia glumae metabolic and signaling pathways within rice tissues through in vivo transcriptome analyses

Burkholderia glumae is a causal agent of rice grain and sheath rot. Similar to other phytopathogens, B. glumae adapts well to the host environment and controls its biology to induce diseases in the host plant; however, its molecular mechanisms are not yet fully understood. To gain a better understating of the actual physiological changes that occur in B. glumae during infection, we analyzed B. glumae transcriptome from infected rice tissues using an RNA-seq technique. To accomplish this, we analyzed differentially expressed genes (DEGs) and identified 2653 transcripts that were significantly altered. We then performed KEGG pathway and module enrichment of the DEGs. Interestingly, most genes involved bacterial chemotaxis-mediated motility, ascorbate and trehalose metabolisms, and sugar transporters including l-arabinose and d-xylose were found to be highly enriched. The in vivo transcriptional profiling of pathogenic B. glumae will facilitate elucidation of unknown plant-pathogenic bacteria interactions, as well as the overall infection processes.