The Plant-Associated Microbe Gene Ontology (PAMGO) Consortium: community development of new Gene Ontology terms describing biological processes involved in microbe-host interactions

New and revised gene ontology biological process terms describe multiorganism interactions critical for understanding microbial pathogenesis and sequences of concern

BACKGROUND

There is a new framework from the United States government for screening synthetic nucleic acids. Beginning in October of 2026, it calls for the screening of sequences 50 nucleotides or greater in length that are known to contribute to pathogenicity or toxicity for humans, regardless of the taxa from which it originates. Distinguishing sequences that encode pathogenic and toxic functions from those that lack them is not simple.

OBJECTIVES

Our project scope was to discern, describe, and catalog sequences involved in microbial pathogenesis from the scientific literature. We recognize a need for better terminology to designate pathogenic functions that are relevant across the entire range of existing parasites.

METHODS

We canvassed publications investigating microbial pathogens of humans, other animals, and some plants to collect thousands of sequences that enable the exploitation of hosts. We compared sequences to each other, grouping them according to what host biological processes they subvert and the consequence(s) for the host. We developed terms to capture many of the varied pathogenic functions for sequences employed by parasitic microbes for host exploitation and applied these terms in a systematic manner to our dataset of sequences.

RESULTS/CONCLUSIONS

The enhanced and expanded terms enable a quick and pertinent evaluation of a sequence's ability to endow a microbe with pathogenic function when they are appropriately applied to relevant sequences. This will allow providers of synthetic nucleic acids to rapidly assess sequences ordered by their customers for pathogenic capacity. This will help fulfill the new US government guidance.

Unraveling plant-microbe interactions: can integrated omics approaches offer concrete answers?

Advances in high throughput omics techniques provide avenues to decipher plant microbiomes. However, there is limited information on how integrated informatics can help provide deeper insights into plant-microbe interactions in a concerted way. Integrating multi-omics datasets can transform our understanding of the plant microbiome from unspecified genetic influences on interacting species to specific gene-by-gene interactions. Here, we highlight recent progress and emerging strategies in crop microbiome omics research and review key aspects of how the integration of host and microbial omics-based datasets can be used to provide a comprehensive outline of complex crop-microbe interactions. We describe how these technological advances have helped unravel crucial plant and microbial genes and pathways that control beneficial, pathogenic, and commensal plant-microbe interactions. We identify crucial knowledge gaps and synthesize current limitations in our understanding of crop microbiome omics approaches. We highlight recent studies in which multi-omics-based approaches have led to improved models of crop microbial community structure and function. Finally, we recommend holistic approaches in integrating host and microbial omics datasets to achieve precision and efficiency in data analysis, which is crucial for biotic and abiotic stress control and in understanding the contribution of the microbiota in shaping plant fitness.

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

The genome and transcriptome of Sarocladium terricola provide insight into ergosterol biosynthesis

Sarocladium terricola is a species of ascomycete fungus that has been recognized as a biocontrol agent for managing animal and plant pathogens, and exhibits significant potential as a feed additive. In this study, we utilized a combination of short-read Illumina sequencing and long-read PacBio sequencing to sequence, assemble, and analyze the genome of S. terricola. The resulting genome consisted of 11 scaffolds encompassing 30.27 Mb, with a GC content of 54.07%, and 10,326 predicted protein coding gene models. We utilized 268 single-copy ortholog genes to reconstruct the phylogenomic relationships among 26 ascomycetes, and found that S. terricola was closely related to two Acremonium species. We also determined that the ergosterol content of S. terricola was synthesized to nearly double levels when cultured in potato dextrose media compared to bean media (4509 mg/kg vs. 2382 mg/kg). Furthermore, transcriptome analyses of differentially expressed genes suggested that the ergosterol synthesis genes ERG3, ERG5, and ERG25 were significantly up-regulated in potato dextrose media. These results will help us to recognize metabolic pathway of ergosterol biosynthesis of S. terricloa comprehensivelly.

Whole genome sequencing of an edible and medicinal mushroom, Russula griseocarnosa, and its association with mycorrhizal characteristics

Russula griseocarnosa is a well-known ectomycorrhizal mushroom, which is mainly distributed in the Southern China. Although several scholars have attempted to isolate and cultivate fungal strains, no accurate method for culture of artificial fruiting bodies has been presented owing to difficulties associated with mycelium growth on artificial media. Herein, we sequenced R. griseocarnosa genome using the second- and third-generation sequencing technologies, followed by de novo assembly of high-throughput sequencing reads, and GeneMark-ES, BLAST, CAZy, and other databases were utilized for functional gene annotation. We also constructed a phylogenetic tree using different species of fungi, and also conducted comparative genomics analysis of R. griseocarnosa against its four representative species. In addition, we evaluated the accuracy of one already sequenced genome of R. griseocarnosa based on the internal transcribed spacer (ITS) sequencing of that type of species. The assembly process resulted in identification of 230 scaffolds with a total genome size of 50.67 Mbp. The gene prediction showed that R. griseocarnosa genome included 14,229 coding sequences (CDs). In addition, 470 RNAs were predicted with 155 transfer RNAs (tRNAs), 49 ribosomal RNAs (rRNAs), 41 small noncoding RNAs (sRNAs), 42 small nuclear RNAs (snRNAs), and 183 microRNAs (miRNAs). The predicted protein sequences of R. griseocarnosa were analyzed to indicate the existence of carbohydrate-active enzymes (CAZymes), and the results revealed that 153 genes encoded CAZymes, which were distributed in 58 CAZyme families. These enzymes included 78 glycoside hydrolases (GHs), 34 glycosyl transferases (GTs), 30 auxiliary activities (AAs), 2 carbohydrate esterases (CEs), 8 carbohydrate-binding modules (CBMs), and only one polysaccharide lyase (PL). Compared with other fungi, R. griseocarnosa had fewer CAZymes, and the number and distribution of CAZymes were similar to other mycorrhizal fungi, such as Tricholoma matsutake and Suillus luteus. Well-defined effector proteins that were associated with mycorrhiza-induced small-secreted proteins (MiSSPs) were not found in R. griseocarnosa, which indicated that there may be some special effector proteins to interact with host plants in R. griseocarnosa. The genome of R. griseocarnosa may provide new insights into the energy metabolism of ectomycorrhizal (ECM) fungi, a reference to study ecosystem and evolutionary diversification of R. griseocarnosa, as well as promoting the study of artificial domestication.

Transcriptome Reveals Roles of Lignin-Modifying Enzymes and Abscisic Acid in the Symbiosis of Mycena and Gastrodia elata

Gastrodia elata is a well-known medicinal and heterotrophic orchid. Its germination, limited by the impermeability of seed coat lignin and inhibition by abscisic acid (ABA), is triggered by symbiosis with fungi such as Mycena spp. However, the molecular mechanisms of lignin degradation by Mycena and ABA biosynthesis and signaling in G. elata remain unclear. In order to gain insights into these two processes, this study analyzed the transcriptomes of these organisms during their dynamic symbiosis. Among the 25 lignin-modifying enzyme genes in Mycena, two ligninolytic class II peroxidases and two laccases were significantly upregulated, most likely enabling Mycena hyphae to break through the lignin seed coats of G. elata. Genes related to reduced virulence and loss of pathogenicity in Mycena accounted for more than half of annotated genes, presumably contributing to symbiosis. After coculture, upregulated genes outnumbered downregulated genes in G. elata seeds, suggesting slightly increased biological activity, while Mycena hyphae had fewer upregulated than downregulated genes, indicating decreased biological activity. ABA biosynthesis in G. elata was reduced by the downregulated expression of 9-cis-epoxycarotenoid dioxygenase (NCED-2), and ABA signaling was blocked by the downregulated expression of a receptor protein (PYL12-like). This is the first report to describe the role of NCED-2 and PYL12-like in breaking G. elata seed dormancy by reducing the synthesis and blocking the signaling of the germination inhibitor ABA. This study provides a theoretical basis for screening germination fungi to identify effective symbionts and for reducing ABA inhibition of G. elata seed germination.

Assembly and annotation of whole-genome sequence of Fusarium equiseti

Fusarium equiseti is a plant pathogen with a wide range of hosts and diverse effects, including probiotic effects. However, the molecular mechanisms underlying these effects remain unclear, hindering its effective utilization. The final assembly included 16 scaffolds of contiguous sequence without gaps. The total sequence length was 40,776,005 bp, and the GC content of 48.01%. In total, we annotated the putative function of 13,134 genes, accounting for 94.97% of the candidate genes. We identified two and 23 candidate genes that are likely involved in the production of mycotoxins zearalenone and trichothecene, respectively. A comparative genomic analysis supported the high quality of the F. equiseti assembly. Our comprehensive analysis of whole-genome sequence will serve as a valuable resource for future studies of expression, regulation, function and evolution of the genes of F. equiseti as well as studies into disease prevention and control.

Deciphering the Omics of Plant-Microbe Interaction: Perspectives and New Insights

Introduction

Plants do not grow in isolation, rather they are hosts to a variety of microbes in their natural environments. While, few thrive in the plants for their own benefit, others may have a direct impact on plants in a symbiotic manner. Unraveling plant-microbe interactions is a critical component in recognizing the positive and negative impacts of microbes on plants. Also, by affecting the environment around plants, microbes may indirectly influence plants. The progress in sequencing technologies in the genomics era and several omics tools has accelerated in biological science. Studying the complex nature of plant-microbe interactions can offer several strategies to increase the productivity of plants in an environmentally friendly manner by providing better insights. This review brings forward the recent works performed in building omics strategies that decipher the interactions between plant-microbiome. At the same time, it further explores other associated mutually beneficial aspects of plant-microbe interactions such as plant growth promotion, nitrogen fixation, stress suppressions in crops and bioremediation; as well as provides better insights on metabolic interactions between microbes and plants through omics approaches. It also aims to explore advances in the study of Arabidopsis as an important avenue to serve as a baseline tool to create models that help in scrutinizing various factors that contribute to the elaborate relationship between plants and microbes. Causal relationships between plants and microbes can be established through systematic gnotobiotic experimental studies to test hypotheses on biologically derived interactions.

Conclusion

This review will cover recent advances in the study of plant-microbe interactions keeping in view the advantages of these interactions in improving nutrient uptake and plant health.

Genome Sequencing and Analysis of the Hypocrellin-Producing Fungus Shiraia bambusicola S4201

Shiraia bambusicola has long been used as a traditional Chinese medicine and its major medicinal active metabolite is hypocrellin, which exhibits outstanding antiviral and antitumor properties. Here we report the 32 Mb draft genome sequence of S. bambusicola S4201, encoding 11,332 predicted genes. The genome of S. bambusicola is enriched in carbohydrate-active enzymes (CAZy) and pathogenesis-related genes. The phylogenetic tree of S. bambusicola S4201 and nine other sequenced species was constructed and its taxonomic status was supported (Pleosporales, Dothideomycetes). The genome contains a rich set of secondary metabolite biosynthetic gene clusters, suggesting that strain S4201 has a remarkable capacity to produce secondary metabolites. Overexpression of the zinc finger transcription factor zftf, which is involved in hypocrellin A (HA) biosynthesis, increases HA production when compared with wild type. In addition, a new putative HA biosynthetic pathway is proposed. These results provide a framework to study the mechanisms of infection in bamboo and to understand the phylogenetic relationships of S. bambusicola S4201. At the same time, knowledge of the genome sequence may potentially solve the puzzle of HA biosynthesis and lead to the discovery of novel genes and secondary metabolites of importance in medicine and agriculture.

Genome Sequence of Lactobacillus futsaii Y97, a Potential Probiotic Strain Isolated from Futsai of Taiwan

Here, we report the complete genome sequence of Lactobacillus futsaii Y97, a potential probiotic strain isolated from futsai of Taiwan. The genome consists of one chromosome of 2.56 Mb and three plasmids. The genome contains 2,622 genes, which make up 87.06% of the genome.

Here, we report the complete genome sequence of Lactobacillus futsaii Y97, a potential probiotic strain isolated from futsai of Taiwan. The genome consists of one chromosome of 2.56 Mb and three plasmids. The genome contains 2,622 genes, which make up 87.06% of the genome.

Comprehensive analysis of full genome sequence and Bd-milRNA/target mRNAs to discover the mechanism of hypovirulence in Botryosphaeria dothidea strains on pear infection with BdCV1 and BdPV1

Pear ring rot disease, mainly caused by Botryosphaeria dothidea, is widespread in most pear and apple-growing regions. Mycoviruses are used for biocontrol, especially in fruit tree disease. BdCV1 (Botryosphaeria dothidea chrysovirus 1) and BdPV1 (Botryosphaeria dothidea partitivirus 1) influence the biological characteristics of B. dothidea strains. BdCV1 is a potential candidate for the control of fungal disease. Therefore, it is vital to explore interactions between B. dothidea and mycovirus to clarify the pathogenic mechanisms of B. dothidea and hypovirulence of B. dothidea in pear. A high-quality full-length genome sequence of the B. dothidea LW-Hubei isolate was obtained using Single Molecule Real-Time sequencing. It has high repeat sequence with 9.3% and DNA methylation existence in the genome. The 46.34 Mb genomes contained 14,091 predicted genes, which of 13,135 were annotated. B. dothidea was predicted to express 3833 secreted proteins. In bioinformatics analysis, 351 CAZy members, 552 transporters, 128 kinases, and 1096 proteins associated with plant-host interaction (PHI) were identified. RNA-silencing components including two endoribonuclease Dicer, four argonaute (Ago) and three RNA-dependent RNA polymerase (RdRp) molecules were identified and expressed in response to mycovirus infection. Horizontal transfer of the LW-C and LW-P strains indicated that BdCV1 induced host gene silencing in LW-C to suppress BdPV1 transmission. To investigate the role of RNA-silencing in B. dothidea defense, we constructed four small RNA libraries and sequenced B. dothidea micro-like RNAs (Bd-milRNAs) produced in response to BdCV1 and BdPV1 infection. Among these, 167 conserved and 68 candidate novel Bd-milRNAs were identified, of which 161 conserved and 20 novel Bd-milRNA were differentially expressed. WEGO analysis revealed involvement of the differentially expressed Bd-milRNA-targeted genes in metabolic process, catalytic activity, cell process and response to stress or stimulus. BdCV1 had a greater effect on the phenotype, virulence, conidiomata, vertical and horizontal transmission ability, and mycelia cellular structure biological characteristics of B. dothidea strains than BdPV1 and virus-free strains. The results obtained in this study indicate that mycovirus regulates biological processes in B. dothidea through the combined interaction of antiviral defense mediated by RNA-silencing and milRNA-mediated regulation of target gene mRNA expression.

Whole Genome Sequence of an Edible and Potential Medicinal Fungus, Cordyceps guangdongensis

Cordyceps guangdongensis is an edible fungus which was approved as a novel food by the Chinese Ministry of Public Health in 2013. It also has a broad prospect of application in pharmaceutical industries, with many medicinal activities. In this study, the whole genome of C. guangdongensis GD15, a single spore isolate from a wild strain, was sequenced and assembled with Illumina and PacBio sequencing technology. The generated genome is 29.05 Mb in size, comprising nine scaffolds with an average GC content of 57.01%. It is predicted to contain a total of 9150 protein-coding genes. Sequence identification and comparative analysis indicated that the assembled scaffolds contained two complete chromosomes and four single-end chromosomes, showing a high level assembly. Gene annotation revealed a diversity of transposons that could contribute to the genome size and evolution. Besides, approximately 15.57% and 12.01% genes involved in metabolic processes were annotated by KEGG and COG respectively. Genes belonging to CAZymes accounted for 3.15% of the total genes. In addition, 435 transcription factors, involved in various biological processes, were identified. Among the identified transcription factors, the fungal transcription regulatory proteins (18.39%) and fungal-specific transcription factors (19.77%) represented the two largest classes of transcription factors. This genomic resource provided a new insight into better understanding the relevance of phenotypic characters and genetic mechanisms in C. guangdongensis.

Excess labile carbon promotes the expression of virulence factors in coral reef bacterioplankton

Coastal pollution and algal cover are increasing on many coral reefs, resulting in higher dissolved organic carbon (DOC) concentrations. High DOC concentrations strongly affect microbial activity in reef waters and select for copiotrophic, often potentially virulent microbial populations. High DOC concentrations on coral reefs are also hypothesized to be a determinant for switching microbial lifestyles from commensal to pathogenic, thereby contributing to coral reef degradation, but evidence is missing. In this study, we conducted ex situ incubations to assess gene expression of planktonic microbial populations under elevated concentrations of naturally abundant monosaccharides (glucose, galactose, mannose, and xylose) in algal exudates and sewage inflows. We assembled 27 near-complete (>70%) microbial genomes through metagenomic sequencing and determined associated expression patterns through metatranscriptomic sequencing. Differential gene expression analysis revealed a shift in the central carbohydrate metabolism and the induction of metalloproteases, siderophores, and toxins in Alteromonas, Erythrobacter, Oceanicola, and Alcanivorax populations. Sugar-specific induction of virulence factors suggests a mechanistic link for the switch from a commensal to a pathogenic lifestyle, particularly relevant during increased algal cover and human-derived pollution on coral reefs. Although an explicit test remains to be performed, our data support the hypothesis that increased availability of specific sugars changes net microbial community activity in ways that increase the emergence and abundance of opportunistic pathogens, potentially contributing to coral reef degradation.

PHI-base: a new interface and further additions for the multi-species pathogen-host interactions database

The pathogen-host interactions database (PHI-base) is available at www.phi-base.org PHI-base contains expertly curated molecular and biological information on genes proven to affect the outcome of pathogen-host interactions reported in peer reviewed research articles. In addition, literature that indicates specific gene alterations that did not affect the disease interaction phenotype are curated to provide complete datasets for comparative purposes. Viruses are not included. Here we describe a revised PHI-base Version 4 data platform with improved search, filtering and extended data display functions. A PHIB-BLAST search function is provided and a link to PHI-Canto, a tool for authors to directly curate their own published data into PHI-base. The new release of PHI-base Version 4.2 (October 2016) has an increased data content containing information from 2219 manually curated references. The data provide information on 4460 genes from 264 pathogens tested on 176 hosts in 8046 interactions. Prokaryotic and eukaryotic pathogens are represented in almost equal numbers. Host species belong ∼70% to plants and 30% to other species of medical and/or environmental importance. Additional data types included into PHI-base 4 are the direct targets of pathogen effector proteins in experimental and natural host organisms. The curation problems encountered and the future directions of the PHI-base project are briefly discussed.

Massive analysis of cDNA ends (MACE) reveals a co-segregating candidate gene for LpPg1 stem rust resistance in perennial ryegrass (Lolium perenne)

Molecular markers including a potential resistance gene co-segregating with the LpPg1 stem rust resistance locus in perennial ryegrass were identified by massive analysis of cDNA ends (MACE) transcriptome profiling. Stem rust caused by Puccinia graminis subsp. graminicola is a severe fungal disease in the forage crop perennial ryegrass and other grasses. The previously identified LpPg1 locus confers efficient resistance against the pathogen. The aim of this study was to identify candidate genes involved in rust resistance and to use them as a resource for the development of molecular markers for LpPg1. To identify such candidates, bulked segregant analysis was combined with NGS-based massive analysis of cDNA ends (MACE) transcriptome profiling. Total RNA was isolated from bulks of infected and non-infected leaf segments from susceptible and resistant genotypes of a full-sibling mapping population and their respective parental lines and MACE was performed. Bioinformatic analysis detected 330 resistance-specific SNPs in 178 transcripts and 341 transcripts that were exclusively expressed in the resistant bulk. The sequences of many of these transcripts were homologous to genes in distinct regions of chromosomes one and four of the model grass Brachypodium distachyon. Of these, 30 were genetically mapped to a 50.8 cM spanning region surrounding the LpPg1 locus. One candidate NBS-LRR gene co-segregated with the resistance locus. Quantitative analysis of gene expression suggests that LpPg1 mediates an efficient resistance mechanism characterized by early recognition of the pathogen, fast defense signaling and rapid induction of antifungal proteins. We demonstrate here that MACE is a cost-efficient, fast and reliable tool that detects polymorphisms for genetic mapping of candidate resistance genes and simultaneously reveals deep insight into the molecular and genetic base of resistance.

Plant Microbe Interactions in Post Genomic Era: Perspectives and Applications

Deciphering plant-microbe interactions is a promising aspect to understand the benefits and the pathogenic effect of microbes and crop improvement. The advancement in sequencing technologies and various 'omics' tool has impressively accelerated the research in biological sciences in this area. The recent and ongoing developments provide a unique approach to describing these intricate interactions and test hypotheses. In the present review, we discuss the role of plant-pathogen interaction in crop improvement. The plant innate immunity has always been an important aspect of research and leads to some interesting information like the adaptation of unique immune mechanisms of plants against pathogens. The development of new techniques in the post - genomic era has greatly enhanced our understanding of the regulation of plant defense mechanisms against pathogens. The present review also provides an overview of beneficial plant-microbe interactions with special reference to Agrobacterium tumefaciens-plant interactions where plant derived signal molecules and plant immune responses are important in pathogenicity and transformation efficiency. The construction of various Genome-scale metabolic models of microorganisms and plants presented a better understanding of all metabolic interactions activated during the interactions. This review also lists the emerging repertoire of phytopathogens and its impact on plant disease resistance. Outline of different aspects of plant-pathogen interactions is presented in this review to bridge the gap between plant microbial ecology and their immune responses.

Location and foraging as basis for classification of biotic interactions

Ecologists face an overwhelming diversity of ecological relationships in natural communities. In this paper, I propose to differentiate various types of the interspecific relations on the basis of two factors: relative localization and foraging activity of interacting partners. I advocate recognition of four types of environments: internal, surface, proximate external and distant external. Then I distinguish four types of synoikia-one partner lives in different degree of proximity to another; and four types of synmensalism: one partner forages in different degree of proximity to another. Intersection of localization-based (four subtypes of synoikia) and foraging-based (four subtypes of synmensalism) rows results in 16 types of interactions. This scheme can serve as a framework that manages diverse biotic interactions in a standardized way. I have made the first step to set up nomenclature standards for terms describing interspecific interactions and hope that this will facilitate research and communication.

Analysis of the Transcriptome of the Infective Stage of the Beet Cyst Nematode, H. schachtii

The beet cyst nematode, Heterodera schachtii, is a major root pest that significantly impacts the yield of sugar beet, brassicas and related species. There has been limited molecular characterisation of this important plant pathogen: to identify target genes for its control the transcriptome of the pre-parasitic J2 stage of H. schachtii was sequenced using Roche GS FLX. Ninety seven percent of reads (i.e., 387,668) with an average PHRED score > 22 were assembled with CAP3 and CLC Genomics Workbench into 37,345 and 47,263 contigs, respectively. The transcripts were annotated by comparing with gene and genomic sequences of other nematodes and annotated proteins on public databases. The annotated transcripts were much more similar to sequences of Heterodera glycines than to those of Globodera pallida and root knot nematodes (Meloidogyne spp.). Analysis of these transcripts showed that a subset of 2,918 transcripts was common to free-living and plant parasitic nematodes suggesting that this subset is involved in general nematode metabolism and development. A set of 148 contigs and 183 singletons encoding putative homologues of effectors previously characterised for plant parasitic nematodes were also identified: these are known to be important for parasitism of host plants during migration through tissues or feeding from cells or are thought to be involved in evasion or modulation of host defences. In addition, the presence of sequences from a nematode virus is suggested. The sequencing and annotation of this transcriptome significantly adds to the genetic data available for H. schachtii, and identifies genes primed to undertake required roles in the critical pre-parasitic and early post-parasitic J2 stages. These data provide new information for identifying potential gene targets for future protection of susceptible crops against H. schachtii.

Genetic resources for advanced biofuel production described with the Gene Ontology

Dramatic increases in research in the area of microbial biofuel production coupled with high-throughput data generation on bioenergy-related microbes has led to a deluge of information in the scientific literature and in databases. Consolidating this information and making it easily accessible requires a unified vocabulary. The Gene Ontology (GO) fulfills that requirement, as it is a well-developed structured vocabulary that describes the activities and locations of gene products in a consistent manner across all kingdoms of life. The Microbial ENergy processes Gene Ontology () project is extending the GO to include new terms to describe microbial processes of interest to bioenergy production. Our effort has added over 600 bioenergy related terms to the Gene Ontology. These terms will aid in the comprehensive annotation of gene products from diverse energy-related microbial genomes. An area of microbial energy research that has received a lot of attention is microbial production of advanced biofuels. These include alcohols such as butanol, isopropanol, isobutanol, and fuels derived from fatty acids, isoprenoids, and polyhydroxyalkanoates. These fuels are superior to first generation biofuels (ethanol and biodiesel esterified from vegetable oil or animal fat), can be generated from non-food feedstock sources, can be used as supplements or substitutes for gasoline, diesel and jet fuels, and can be stored and distributed using existing infrastructure. Here we review the roles of genes associated with synthesis of advanced biofuels, and at the same time introduce the use of the GO to describe the functions of these genes in a standardized way.

PPDB - A tool for investigation of plants physiology based on gene ontology

Representing the way forward, from functional genomics and its ontology to functional understanding and physiological model, in a computationally tractable fashion is one of the ongoing challenges faced by computational biology. To tackle the standpoint, we herein feature the applications of contemporary database management to the development of PPDB, a searching and browsing tool for the Plants Physiology Database that is based upon the mining of a large amount of gene ontology data currently available. The working principles and search options associated with the PPDB are publicly available and freely accessible on-line ( http://www.iitr.ernet.in/ajayshiv/ ) through a user friendly environment generated by means of Drupal-6.24. By knowing that genes are expressed in temporally and spatially characteristic patterns and that their functionally distinct products often reside in specific cellular compartments and may be part of one or more multi-component complexes, this sort of work is intended to be relevant for investigating the functional relationships of gene products at a system level and, thus, helps us approach to the full physiology.

Silicon era of carbon-based life: application of genomics and bioinformatics in crop stress research

Abiotic and biotic stresses lead to massive reprogramming of different life processes and are the major limiting factors hampering crop productivity. Omics-based research platforms allow for a holistic and comprehensive survey on crop stress responses and hence may bring forth better crop improvement strategies. Since high-throughput approaches generate considerable amounts of data, bioinformatics tools will play an essential role in storing, retrieving, sharing, processing, and analyzing them. Genomic and functional genomic studies in crops still lag far behind similar studies in humans and other animals. In this review, we summarize some useful genomics and bioinformatics resources available to crop scientists. In addition, we also discuss the major challenges and advancements in the "-omics" studies, with an emphasis on their possible impacts on crop stress research and crop improvement.

Improved gene ontology annotation for biofilm formation, filamentous growth, and phenotypic switching in Candida albicans

The opportunistic fungal pathogen Candida albicans is a significant medical threat, especially for immunocompromised patients. Experimental research has focused on specific areas of C. albicans biology, with the goal of understanding the multiple factors that contribute to its pathogenic potential. Some of these factors include cell adhesion, invasive or filamentous growth, and the formation of drug-resistant biofilms. The Gene Ontology (GO) (www.geneontology.org) is a standardized vocabulary that the Candida Genome Database (CGD) (www.candidagenome.org) and other groups use to describe the functions of gene products. To improve the breadth and accuracy of pathogenicity-related gene product descriptions and to facilitate the description of as yet uncharacterized but potentially pathogenicity-related genes in Candida species, CGD undertook a three-part project: first, the addition of terms to the biological process branch of the GO to improve the description of fungus-related processes; second, manual recuration of gene product annotations in CGD to use the improved GO vocabulary; and third, computational ortholog-based transfer of GO annotations from experimentally characterized gene products, using these new terms, to uncharacterized orthologs in other Candida species. Through genome annotation and analysis, we identified candidate pathogenicity genes in seven non-C. albicans Candida species and in one additional C. albicans strain, WO-1. We also defined a set of C. albicans genes at the intersection of biofilm formation, filamentous growth, pathogenesis, and phenotypic switching of this opportunistic fungal pathogen, which provides a compelling list of candidates for further experimentation.

Ranking Gene Ontology terms for predicting non-classical secretory proteins in eukaryotes and prokaryotes

Protein secretion is an important biological process for both eukaryotes and prokaryotes. Several sequence-based methods mainly rely on utilizing various types of complementary features to design accurate classifiers for predicting non-classical secretory proteins. Gene Ontology (GO) terms are increasing informative in predicting protein functions. However, the number of used GO terms is often very large. For example, there are 60,020 GO terms used in the prediction method Euk-mPLoc 2.0 for subcellular localization. This study proposes a novel approach to identify a small set of m top-ranked GO terms served as the only type of input features to design a support vector machine (SVM) based method Sec-GO to predict non-classical secretory proteins in both eukaryotes and prokaryotes. To evaluate the Sec-GO method, two existing methods and their used datasets are adopted for performance comparisons. The Sec-GO method using m=436 GO terms yields an independent test accuracy of 96.7% on mammalian proteins, much better than the existing method SPRED (82.2%) which uses frequencies of tri-peptides and short peptides, secondary structure, and physicochemical properties as input features of a random forest classifier. Furthermore, when applying to Gram-positive bacterial proteins, the Sec-GO with m=158 GO terms has a test accuracy of 94.5%, superior to NClassG+ (90.0%) which uses SVM with several feature types, comprising amino acid composition, di-peptides, physicochemical properties and the position specific weighting matrix. Analysis of the distribution of secretory proteins in a GO database indicates the percentage of the non-classical secretory proteins annotated by GO is larger than that of classical secretory proteins in both eukaryotes and prokaryotes. Of the m top-ranked GO features, the top-four GO terms are all annotated by such subcellular locations as GO:0005576 (Extracellular region). Additionally, the method Sec-GO is easily implemented and its web tool of prediction is available at iclab.life.nctu.edu.tw/secgo.

Unraveling plant-microbe interactions: can multi-species transcriptomics help?

Plants in their natural habitats are surrounded by a large number of microorganisms. Some microbes directly interact with plants in a mutually beneficial manner whereas others colonize the plant only for their own benefit. In addition, microbes can indirectly affect plants by drastically altering their environments. Understanding the complex nature of plant-microbe interactions can potentially offer new strategies to enhance plant productivity in an environmentally friendly manner. As briefly reviewed here, the emerging area of multi-species transcriptomics holds the promise to provide knowledge on how this can be achieved. We discuss key aspects of how transcriptome analysis can be used to provide a more comprehensive picture of the complex interactions of plants with their biotic and abiotic environments.

The UniProt-GO Annotation database in 2011

The GO annotation dataset provided by the UniProt Consortium (GOA: http://www.ebi.ac.uk/GOA) is a comprehensive set of evidenced-based associations between terms from the Gene Ontology resource and UniProtKB proteins. Currently supplying over 100 million annotations to 11 million proteins in more than 360 000 taxa, this resource has increased 2-fold over the last 2 years and has benefited from a wealth of checks to improve annotation correctness and consistency as well as now supplying a greater information content enabled by GO Consortium annotation format developments. Detailed, manual GO annotations obtained from the curation of peer-reviewed papers are directly contributed by all UniProt curators and supplemented with manual and electronic annotations from 36 model organism and domain-focused scientific resources. The inclusion of high-quality, automatic annotation predictions ensures the UniProt GO annotation dataset supplies functional information to a wide range of proteins, including those from poorly characterized, non-model organism species. UniProt GO annotations are freely available in a range of formats accessible by both file downloads and web-based views. In addition, the introduction of a new, normalized file format in 2010 has made for easier handling of the complete UniProt-GOA data set.

The RICORDO approach to semantic interoperability for biomedical data and models: strategy, standards and solutions

Background

The practice and research of medicine generates considerable quantities of data and model resources (DMRs). Although in principle biomedical resources are re-usable, in practice few can currently be shared. In particular, the clinical communities in physiology and pharmacology research, as well as medical education, (i.e. PPME communities) are facing considerable operational and technical obstacles in sharing data and models.

Findings

We outline the efforts of the PPME communities to achieve automated semantic interoperability for clinical resource documentation in collaboration with the RICORDO project. Current community practices in resource documentation and knowledge management are overviewed. Furthermore, requirements and improvements sought by the PPME communities to current documentation practices are discussed. The RICORDO plan and effort in creating a representational framework and associated open software toolkit for the automated management of PPME metadata resources is also described.

Conclusions

RICORDO is providing the PPME community with tools to effect, share and reason over clinical resource annotations. This work is contributing to the semantic interoperability of DMRs through ontology-based annotation by (i) supporting more effective navigation and re-use of clinical DMRs, as well as (ii) sustaining interoperability operations based on the criterion of biological similarity. Operations facilitated by RICORDO will range from automated dataset matching to model merging and managing complex simulation workflows. In effect, RICORDO is contributing to community standards for resource sharing and interoperability.

Unifying themes in microbial associations with animal and plant hosts described using the gene ontology

Microbes form intimate relationships with hosts (symbioses) that range from mutualism to parasitism. Common microbial mechanisms involved in a successful host association include adhesion, entry of the microbe or its effector proteins into the host cell, mitigation of host defenses, and nutrient acquisition. Genes associated with these microbial mechanisms are known for a broad range of symbioses, revealing both divergent and convergent strategies. Effective comparisons among these symbioses, however, are hampered by inconsistent descriptive terms in the literature for functionally similar genes. Bioinformatic approaches that use homology-based tools are limited to identifying functionally similar genes based on similarities in their sequences. An effective solution to these limitations is provided by the Gene Ontology (GO), which provides a standardized language to describe gene products from all organisms. The GO comprises three ontologies that enable one to describe the molecular function(s) of gene products, the biological processes to which they contribute, and their cellular locations. Beginning in 2004, the Plant-Associated Microbe Gene Ontology (PAMGO) interest group collaborated with the GO consortium to extend the GO to accommodate terms for describing gene products associated with microbe-host interactions. Currently, over 900 terms that describe biological processes common to diverse plant- and animal-associated microbes are incorporated into the GO database. Here we review some unifying themes common to diverse host-microbe associations and illustrate how the new GO terms facilitate a standardized description of the gene products involved. We also highlight areas where new terms need to be developed, an ongoing process that should involve the whole community.

A genotype and phenotype database of genetically modified malaria-parasites

The RMgm database, www.pberghei.eu, is a web-based, manually curated, repository containing information on genetically modified rodent-malaria parasites. It provides easy and rapid access to information on the genotype and phenotype of mutant and reporter parasites. The database also contains information on unpublished mutants without a clear phenotype and negative trials to disrupt genes. Information can be searched using pre-defined key features, such as phenotype, life-cycle stage, gene model, gene-tags and mutations. The information relating to the mutants is reciprocally linked to PlasmoDB and GeneDB. Access to mutant-parasite information, and gene function/ontology inferred from mutant phenotypes provides a timely resource aimed at enhancing research into Plasmodium gene function and (systems) biology.

Studying plant-pathogen interactions in the genomics era: beyond molecular Koch's postulates to systems biology

Molecular factors enabling microbial pathogens to cause plant diseases have been sought with increasing efficacy over three research eras that successively introduced the tools of disease physiology, single-gene molecular genetics, and genomics. From this work emerged a unified model of the interactions of biotrophic and hemibiotrophic pathogens, which posits that successful pathogens typically defeat two levels of plant defense by translocating cytoplasmic effectors that suppress the first defense (surface arrayed against microbial signatures) while evading the second defense (internally arrayed against effectors). As is predicted from this model and confirmed by sequence pattern-driven discovery of large repertoires of cytoplasmic effectors in the genomes of many pathogens, the coevolution of (hemi)biotrophic pathogens and their hosts has generated pathosystems featuring extreme complexity and apparent robustness. These findings highlight the need for a fourth research era of systems biology in which virulence factors are studied as pathosystem components, and pathosystems are studied for their emergent properties.

Computational techniques for elucidating plant-pathogen interactions from large-scale experiments on fungi and oomycetes

Eukaryotic plant pathogens are responsible for the destruction of billions of dollars worth of crops each year. With large-scale genomics of both pathogens and hosts and the corresponding computational analysis, biologists are now able to gain knowledge about many pathogenic and defense genes concurrently. To study the interactions between these two organism groups, it is necessary to design experiments to elucidate the genes being expressed during the invasion of the pathogen into the host. For the most part, this does not require new software development, though it does require the use of existing software in novel ways. This article provides a broad overview of several key and illustrative experiments and the corresponding computational analyses, outlining the knowledge gained in each. It goes on to describe databases for plant-pathogen data and important initiatives such as Plant-Associated Microbe Gene Ontology. It discusses how various emerging approaches will increase the power of computers in host-pathogen interaction studies.

The Gene Ontology Consortium. The Gene Ontology in 2010: extensions and refinements

The Gene Ontology (GO) Consortium (http://www.geneontology.org) (GOC) continues to develop, maintain and use a set of structured, controlled vocabularies for the annotation of genes, gene products and sequences. The GO ontologies are expanding both in content and in structure. Several new relationship types have been introduced and used, along with existing relationships, to create links between and within the GO domains. These improve the representation of biology, facilitate querying, and allow GO developers to systematically check for and correct inconsistencies within the GO. Gene product annotation using GO continues to increase both in the number of total annotations and in species coverage. GO tools, such as OBO-Edit, an ontology-editing tool, and AmiGO, the GOC ontology browser, have seen major improvements in functionality, speed and ease of use.

A "repertoire for repertoire" hypothesis: repertoires of type three effectors are candidate determinants of host specificity in Xanthomonas

Background

The genetic basis of host specificity for animal and plant pathogenic bacteria remains poorly understood. For plant pathogenic bacteria, host range is restricted to one or a few host plant species reflecting a tight adaptation to specific hosts.

Methodology/Principal Findings

Two hypotheses can be formulated to explain host specificity: either it can be explained by the phylogenetic position of the strains, or by the association of virulence genes enabling a pathological convergence of phylogenically distant strains. In this latter hypothesis, host specificity would result from the interaction between repertoires of bacterial virulence genes and repertoires of genes involved in host defences. To challenge these two hypotheses, we selected 132 Xanthomonas axonopodis strains representative of 18 different pathovars which display different host range. First, the phylogenetic position of each strain was determined by sequencing the housekeeping gene rpoD. This study showed that many pathovars of Xanthomonas axonopodis are polyphyletic. Second, we investigated the distribution of 35 type III effector genes (T3Es) in these strains by both PCR and hybridization methods. Indeed, for pathogenic bacteria T3Es were shown to trigger and to subvert host defences. Our study revealed that T3E repertoires comprise core and variable gene suites that likely have distinct roles in pathogenicity and different evolutionary histories. Our results showed a correspondence between composition of T3E repertoires and pathovars of Xanthomonas axonopodis. For polyphyletic pathovars, this suggests that T3E genes might explain a pathological convergence of phylogenetically distant strains. We also identified several DNA rearrangements within T3E genes, some of which correlate with host specificity of strains.

Conclusions/Significance

These data provide insight into the potential role played by T3E genes for pathogenic bacteria and support a “repertoire for repertoire” hypothesis that may explain host specificity. Our work provides resources for functional and evolutionary studies aiming at understanding host specificity of pathogenic bacteria, functional redundancy between T3Es and the driving forces shaping T3E repertoires.

Infection strategies of filamentous microbes described with the Gene Ontology

Filamentous microbes that form highly developed symbiotic associations (ranging from pathogenesis to mutualism) with their hosts include fungi, oomycetes and actinomycete bacteria. These organisms share many common features in growth, development and infection and have evolved similar strategies for neutralizing host defense responses to establish symbioses. Recent advances in sequencing technologies have led to a remarkable increase in the number of sequenced genomes of filamentous organisms. Analysis of the available genomes has provided useful information about genes that might be important for host infection and colonization. However, because many functional similarities among these organisms have arisen by convergent evolution, sequence-based genomic comparisons will miss many genes that are functionally analogous. In the absence of sequence similarity, annotating genes with standardized terms from the Gene Ontology (GO) can facilitate functional comparisons. Here, we review common strategies employed by filamentous organisms during colonization of their hosts, with reference to GO terms that best describe the processes involved.

Controlled vocabularies for microbial virulence factors

Knowledge about pathogenesis is increasing dramatically, and most of this information is stored in the scientific literature or in sequence databases. This information can be made more accessible by the use of ontologies or controlled vocabularies. Recently, several ontologies, controlled vocabularies and databases have been developed or adapted for virulence factors and their roles in pathogenesis. Here, we discuss these systems, how they are being used in research and the challenges that remain for developing and applying ontologies for virulence factors.

Understanding animal viruses using the Gene Ontology

Understanding the effects of viral infection has typically focused on specific virus-host interactions such as tissue tropism, immune responses and histopathology. However, modeling viral pathogenesis requires information about the functions of gene products from both virus and host, and how these products interact. Recent developments in the functional annotation of genomes using Gene Ontology (GO) and in modeling functional interactions among gene products, together with an increased interest in systems biology, provide an excellent opportunity to generate global interaction models for viral infection. Here, we review how the GO is being used to model viral pathogenesis, with a focus on animal viruses.

What we can learn about Escherichia coli through application of Gene Ontology

How we classify the genes, products and complexes that are present or absent in genomes, transcriptomes, proteomes and other datasets helps us place biological objects into subsystems with common functions, see how molecular functions are used to implement biological processes and compare the biology of different species and strains. Gene Ontology (GO) is one of the most successful systems for classifying biological function. Although GO is widely used for eukaryotic genomics, it has not yet been widely used for bacterial systems. The potential applications of GO are currently limited by the need to improve the annotation of bacterial genomes with GO and to improve how prokaryotic biology is represented in the ontology. Here, we discuss why GO should be adopted by microbiologists, and describe recent efforts to build and maintain high-quality GO annotation for Escherichia coli as a model system.

Describing commonalities in microbial effector delivery using the Gene Ontology

Myriad symbiotic microbes, ranging from mutualistic through to pathogenic, deliver 'effector' molecules into the cytoplasm or cellular milieu of their hosts to facilitate colonization. Among ecologically and evolutionarily diverse taxa, analogous processes and structures exist to facilitate effector delivery. These include syringe-like injection (bacteria and nematodes), common host-targeting signals (oomycetes and protozoans) and specialized intercellular structures (fungi and oomycetes). Here, we briefly introduce readers to the Gene Ontology (GO), a controlled vocabulary to facilitate comparative genomics of diverse taxa. We also summarize and compare selected mechanisms of effector delivery from various organisms and show how careful annotation of gene products with GO can reveal underlying similarities among diverse taxa.

Programmed cell death in host-symbiont associations, viewed through the Gene Ontology

Manipulation of programmed cell death (PCD) is central to many host microbe interactions. Both plant and animal cells use PCD as a powerful weapon against biotrophic pathogens, including viruses, which draw their nutrition from living tissue. Thus, diverse biotrophic pathogens have evolved many mechanisms to suppress programmed cell death, and mutualistic and commensal microbes may employ similar mechanisms. Necrotrophic pathogens derive their nutrition from dead tissue, and many produce toxins specifically to trigger programmed cell death in their hosts. Hemibiotrophic pathogens manipulate PCD in a most exquisite way, suppressing PCD during the biotrophic phase and stimulating it during the necrotrophic phase. This mini-review will summarize the mechanisms that have evolved in diverse microbes and hosts for controlling PCD and the Gene Ontology terms developed by the Plant-Associated Microbe Gene Ontology (PAMGO) Consortium for describing those mechanisms.

Protein secretion systems in bacterial-host associations, and their description in the Gene Ontology

Protein secretion plays a central role in modulating the interactions of bacteria with their environments. This is particularly the case when symbiotic bacteria (whether pathogenic, commensal or mutualistic) are interacting with larger host organisms. In the case of Gram-negative bacteria, secretion requires translocation across the outer as well as the inner membrane, and a diversity of molecular machines have been elaborated for this purpose. A number of secreted proteins are destined to enter the host cell (effectors and toxins), and thus several secretion systems include apparatus to translocate proteins across the plasma membrane of the host also. The Plant-Associated Microbe Gene Ontology (PAMGO) Consortium has been developing standardized terms for describing biological processes and cellular components that play important roles in the interactions of microbes with plant and animal hosts, including the processes of bacterial secretion. Here we survey bacterial secretion systems known to modulate interactions with host organisms and describe Gene Ontology terms useful for describing the components and functions of these systems, and for capturing the similarities among the diverse systems.

Common themes in nutrient acquisition by plant symbiotic microbes, described by the Gene Ontology

A critical function for symbionts is the acquisition of nutrients from their host. Relationships between hosts and symbionts range from biotrophic mutualism to necrotrophic parasitism, with a corresponding range of structures to facilitate nutrient flow between host and symbiont. Here, we review common themes among the nutrient acquisition strategies of a range of plant symbiotic microorganisms, including mutualistic symbionts, biotrophic pathogens that feed from living tissue, necrotrophic pathogens that kill host tissue, and hemibiotrophic pathogens that switch from biotrophy to necrotrophy. We show how Gene Ontology (GO) terms developed by the Plant-Associated Microbe Gene Ontology (PAMGO) Consortium can be used for describing commonalities in nutrient acquisition among diverse plant symbionts. Where appropriate, parallels found among animal symbionts are also highlighted.

Common and contrasting themes in host cell-targeted effectors from bacterial, fungal, oomycete and nematode plant symbionts described using the Gene Ontology

A wide diversity of plant-associated symbionts, including microbes, produce proteins that can enter host cells, or are injected into host cells in order to modify the physiology of the host to promote colonization. These molecules, termed effectors, commonly target the host defense signaling pathways in order to suppress the defense response. Others target the gene expression machinery or trigger specific modifications to host morphology or physiology that promote the nutrition and proliferation of the symbiont. When recognized by the host's surveillance machinery, which includes cognate resistance (R) gene products, defense responses are engaged to restrict pathogen proliferation. Effectors from diverse symbionts may be delivered into plant cells via varied mechanisms, including whole organism cellular entry (viruses, some bacteria and fungi), type III and IV secretion (in bacteria), physical injection (nematodes and insects) and protein translocation signal sequences (oomycetes and fungi). This mini-review will summarize both similarities and differences in effectors and effector delivery systems found in diverse plant-associated symbionts as well as how these are described with Plant-Associated Microbe Gene Ontology (PAMGO) terms.

The Plant-Associated Microbe Gene Ontology (PAMGO) Consortium: community development of new Gene Ontology terms describing biological processes involved in microbe-host interactions

All microbes that form beneficial, neutral, or pathogenic associations with hosts face similar challenges. They must physically adhere to and/or gain entry to host tissues; they must avoid, suppress, or tolerate host defenses; they must acquire nutrients from the host and successfully multiply. Microbes that associate with hosts come from many kingdoms of life and include bacteria, fungi, oomycetes, and nematodes. The increasing numbers of full genome sequences from these diverse microbes provide the opportunity to discover common mechanisms by which the microbes forge and maintain intimate associations with host organisms. However, cross-genome analyses have been hindered by lack of a universal vocabulary for describing biological processes involved in the interplay between microbes and their hosts. The Plant-Associated Microbe Gene Ontology (PAMGO) Consortium has been working for three years as an official interest group of the Gene Ontology (GO) Consortium to develop well-defined GO terms that describe many of the biological processes common to diverse plant- and animal-associated microbes. Creating these terms, over 700 at this time, has required a synthesis of diverse points of view from many research communities. The use of these terms in genome annotation will allow cross-genome searches for genes with common function (without demand for sequence similarity) and also improve the interpretation of data from high-throughput microarray and proteomic analyses. This article, and the more focused mini-reviews that make up this supplement to BMC Microbiology, describe the development and use of these terms.