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Dual-transcriptomic analysis of human nasal transcriptome and microbiome reveals host-bacteria associations in symptomatic respiratory infection.

BACKGROUND: The human nasopharynx is colonized by a diverse community of commensal microbiota linked to many respiratory diseases, yet their associations with the host remain unclear. RESULTS: In this study, we introduced a dual-transcriptomics analysis strategy, which can characterize the host transcriptome and microbiome from nasal samples simultaneously. We applied this workflow to a local SARS-CoV-2 cohort with 76 asymptomatic infected patients, among whom 52 (68.42%) developed symptomatic infection during a 1-week follow-up period. Nasal swabs were collected from all 76 patients at enrollment and from 73 patients at one-week later follow-up. We detected a median of 8.94% reads that did not map to the human genome across all 149 samples, among which around half (median 49.68%) were successfully mapped to microbiome genome. Meta-transcriptomic analysis detected significantly higher SARS-related coronavirus loads in samples from the symptomatic group at enrollment (P&#x2009;=&#x2009;0.004), and both groups showed decreased loads one week later (symptomatic, P&#x2009;=&#x2009;0.001; asymptomatic, P&#x2009;=&#x2009;0.035). Compared with benchmarking 16&#xa0;S rRNA sequencing on 53 samples, our computational strategy showed high correlation of relative abundance in all top 20 genera (median Rho&#x2009;=&#x2009;0.90, Pmax < 0.001). A total of 670 bacteria species were identified to show a relative abundance&#x2009;&#x2265;&#x2009;0.01% in at least 10% samples. Differential abundance analysis identified 76 species (DASs) from six phyla with significantly decreased abundance in samples from the symptomatic group (log2(fold change or FC) < -1 and adjusted P&#x2009;<&#x2009;0.05) compared to the asymptomatic group at enrollment. Integrating these symptom-associated DASs with host's gene expression using an expression quantitative trait bacteria (eQTB) model, we found 45 symptom-associated DASs identified at enrollment were significantly associated with one to 14 genes (adjusted P&#x2009;<&#x2009;0.05). GSEA showed a series of symptom-associated DASs were significantly correlated with pathways related to olfactory function, keratinocyte differentiation, and DNA methylation. CONCLUSIONS: In summary, our dual-transcriptomic analysis strategy effectively characterized host-microbiome associations, offering insights into microbial contributions to respiratory diseases.

Humans↗

Preparation of planar retinal specimens: verification by histology, mRNA profiling, and proteome analysis.

PURPOSE: Elucidation of the transcriptome and proteome of the normal retina will be difficult since it is comprised of at least 55 different cell types. However the characteristic layered cellular anatomy of the retina makes it amenable to planar sectioning, enabling the generation of enriched retinal cell populations. The aim of this study was to validate a reproducible method for preparing enriched retinal layers from porcine retina. METHODS: The thicknesses of the retinal photoreceptor, inner nuclear and ganglion cell, and fiber layers were determined by routine histology of cross sections of fresh whole retina mounted on polyvinylidene difluoride (PVDF) membrane. Dissected retina (5 mm2) was placed on PVDF membrane and a series of planar cryosections corresponding to the photoreceptor and inner nuclear layer were removed leaving the ganglion cell and fiber layer which was subsequently detached from the membrane. The retinal specimens were stored at -80 degrees C. Representative planar tissue sections were sonicated in ice-chilled 40 mM ammonium bicarbonate pH 7.9 and aliquots removed for RNA extraction. Quantitative RT-PCR was used to analyze the mRNA expression of genes indicative of specific retinal layers. Ammonium bicarbonate protein extracts were centrifuged, lyophilized and prepared for direct liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis using a Waters Q-Tof Ultima. RESULTS: Histological analysis established the parameters for planar cryosectioning: photoreceptor layer (69+/-1.8 microm), outer plexiform (11+/-0.6 microm), inner nuclear layer (28+/-0.5 microm), inner plexiform, ganglion cell and fiber layer (100+/-5.3 microm). Gene expression profiling provided an independent method for validating the respective retinal preparations. For example, glial fibrillary acidic protein (GFAP) was expressed up to 21 fold higher in the inner retinal "ganglion cell enriched" fraction than in the outer retinal "photoreceptor enriched" fraction. The pattern was reversed for blue cone opsin, which was expressed up to 24 fold higher in the "photoreceptor enriched" fraction. Endogenous protein fragments indicative of each layer were identified by mass spectrometry and de novo sequence data obtained. CONCLUSIONS: Combined histological and mRNA expression profiling has confirmed the development of a reproducible method for generating validated porcine retinal layers enriched for specific cell types. Direct proteome analysis detected endogenous peptide fragments of characteristic retinal proteins. Further analysis of these enriched retinal cell preparations will facilitate a more selective investigation of the retinal transcriptome and proteome than studies of the intact retina.

Anatomy, Cross-Sectional↗

Impact of haloperidol and risperidone on gene expression profile in the rat cortex.

Despite the clinical efficacy of the most thoroughly studied conventional neuroleptic agent haloperidol, and the atypical antipsychotic risperidone is well established, little information is available on their molecular effects. Recent advances in high-density DNA microarray techniques allow the possibility to analyze thousands of genes simultaneously for their differential gene expression patterns in various biological processes, and to determine mechanisms of drug action. The aim of this series of experiments was to gain experience in antipsychotic gene-expression profiling and characterize (in the parlance of genomics) the "antipsychotic transcriptome." In this prospective animal study, broad-scale gene expression profiles were characterized for brains of rats treated with antipsychotics and compared with those of sham controls. We used DNA microarrays containing 8000 sequences to measure the expression patterns of multiple genes in rat fronto-temporo-parietal cortex after intraperitoneal treatment with haloperidol or risperidone. A number of transcripts were differentially expressed between control and treated samples, of which only 36 and 89 were found to significantly differ in expression as a result of exposure to haloperidol or risperidone, respectively (P<0.05). Acutely, 13 genes were more highly expressed and 15 transcripts were found to be significantly less abundant, whereas chronically nine genes were up-regulated and none of them was repressed in haloperidol-treated cortices. Risperidone acutely induced 43 and repressed 46 genes, and chronically over-expressed 6 and down-regulated 11 transcripts. Selected genes were assayed by real-time PCR, then normalized to beta-actin. These assays confirmed the significance of the array results for all transcripts tested. Despite their differing receptor affinity and selectivity, our findings indicate that haloperidol and risperidone interfere with cell survival, neural plasticity, signal transduction, ionic homeostasis and metabolism in a similar manner.

Animals↗

Single cell RNA sequencing provides novel cellular transcriptional profiles and underlying pathogenesis of presbycusis.

Age-related hearing loss (ARHL) or presbycusis is associated with irreversible progressive damage in the inner ear, where the sound is transduced into electrical signal; but the detailed mechanism remains unclear. Here, we sought to determine the potential molecular mechanism involved in the pathogeneses of ARHL with bioinformatics methods. A single-cell transcriptome sequencing study was performed on the cochlear samples from young and aged mice. Detection of identified cell type marker allowed us to screen 18 transcriptional clusters, including myeloid cells, epithelial cells, B cells, endothelial cells, fibroblasts, T cells, inner pillar cells, neurons, inner phalangeal cells, and red blood cells. Cell-cell communications were analyzed between young and aged cochlear tissue samples by using the latest integration algorithms Cellchat. A total of 56 differentially expressed genes were screened between the two groups. Functional enrichment analysis showed these genes were mainly involved in immune, oxidative stress, apoptosis, and metabolic processes. The expression levels of crucial genes in cochlear tissues were further verified by immunohistochemistry. Overall, this study provides new theoretical support for the development of clinical therapeutic drugs.

Animals↗

PotatoRTD and TomatoRTD: Comprehensive Reference Transcript Datasets for Accurate Transcriptome Analysis and Isoform Discovery.

Transcriptome annotations provide essential information on transcript locations, sequences and structures, including transcription start, end sites and splice junctions. They underpin key biological analyses such as gene and transcript quantification, and the study of transcriptional and post-transcriptional regulation, including alternative transcription initiation, polyadenylation and splicing. Accurate characterisation of transcript isoforms is critical for understanding how gene expression relates to functional protein products. However, for many species-including Solanaceae crops such as potato and tomato-current annotations suffer from limited isoform coverage, with tens or hundreds of thousands of splice junctions and transcript isoforms missing. This undermines the completeness and accuracy of transcript-level analyses. Here, by generating Iso-seq and RNA-seq on a range of tissues and samples, we have produced transcriptome annotations for both potato and tomato with improved coverage, diversity, accurate splice junctions, and transcript start and end sites. We have also made these high-quality resources accessible through genome browsers. These enhanced annotations will enable more accurate transcriptome analyses, supporting higher-resolution and novel biological discoveries.

Solanum tuberosum↗

Paired Single-Cell Transcriptome and DNA Barcode Detection in Zebrafish Using ScarTrace.

ScarTrace is a CRISPR/Cas9-based genetic lineage tracing method that allows for uniquely barcoding the DNA of single cells at a target GFP sequence during developing zebrafish embryos. Single cells from barcoded adult zebrafish can be isolated from various tissues (e.g., marrow, brain, eyes, fins), and their transcriptome and barcode sequences are captured by single-cell cDNA amplification and genomic DNA nested PCR, respectively. Computationally, cell type and barcode identification permit clone tracing and lineage tree reconstruction of tissues to unravel fate decisions during embryogenesis.

Animals↗

Uncovering hidden complexity in the Apis mellifera mitotranscriptome: a polyadenylation-centered perspective.

Mitochondrial transcription is gaining increasing attention as researchers seek to better understand the full coding potential of mitochondrial DNA (mtDNA). Emerging evidence suggests that mtDNA may encode additional elements beyond classical oxidative phosphorylation genes, pointing to a more complex transcriptional architecture than previously recognized. In this study, we explored the mitochondrial transcriptome of Apis mellifera (Insecta: Hymenoptera), with a particular focus on polyadenylation-associated features. Our analysis revealed that both sense and antisense transcripts undergo polyadenylation, although transcript abundance and poly(A) tail lengths varied markedly across mitochondrial genes. Several transcripts exhibited alternative isoforms, either extended or truncated, frequently including intergenic regions. These regions may represent functional non-coding elements or structural variants rather than conventional untranslated regions (UTRs). Interestingly, some transcripts also contained non-templated nucleotide additions particularly cytosine residues immediately upstream of the poly(A) tails. Monocistronic units that included portions of downstream intergenic regions were among the most abundantly represented, suggesting a possible regulatory role for these sequences. To experimentally validate our in silico findings, we performed RT-qPCR to assess relative gene expression and applied 3' RACE-PCR to define transcript boundaries. These approaches confirmed the presence of multiple transcript isoforms and supported the involvement of polyadenylation in shaping mitochondrial RNA diversity. Together, our findings reveal a previously underappreciated level of complexity in the A. mellifera mitochondrial transcriptome and highlight the potential regulatory significance of polyadenylation dynamics and intergenic region transcription.

Animals↗

Tag-based approaches for transcriptome research and genome annotation.

With the increasing number of whole genome sequences available, genomic research has shifted toward the annotation of functional elements and transcribed regions. Thus, the related field of transcriptome research requires accurate methods for the profiling of genes that are not biased by known sequence information, and that also allow for the identification of promoter regions. Starting with serial analysis of gene expression (SAGE), methods making use of short sequencing tags have greatly contributed to transcriptome studies. Here we review recent developments in the use of short sequencing tags in expression profiling, gene discovery and genome annotation. These tags are obtained from the 5' end of mRNAs, both terminal ends of mRNAs, or genomic regions. The 5' end-specific tags, with their ability to identify transcripts along with their transcriptional start sites, will be of particular interest for gene network studies and may become one of the most important approaches in systems biology.

Animals↗

Functional genomic analysis of midgut epithelial responses in Anopheles during Plasmodium invasion.

BACKGROUND: The malaria parasite Plasmodium must complete a complex developmental life cycle within Anopheles mosquitoes before it can be transmitted into the human host. One day after mosquito infection, motile ookinetes traverse the midgut epithelium and, after exiting to its basal site facing the hemolymph, develop into oocysts. Previously, we have identified hemolymph factors that can antagonize or promote parasite development. RESULTS: We profiled on a genomic scale the transcriptional responses of the A. gambiae midgut to P. berghei and showed that more than 7% of the assessed mosquito transcriptome is differentially regulated during invasion. The profiles suggested that actin- and microtubule-cytoskeleton remodeling is a major response of the epithelium to ookinete penetration. Other responses encompass components of innate immunity, extracellular-matrix remodeling, and apoptosis. RNAi-dependent gene silencing identified both parasite antagonists and agonists among regulators of actin dynamics and revealed that actin polymerization is inhibitory to the invading parasite. Combined transcriptional and reverse-genetic analysis further identified an unexpected dual role of the lipid-trafficking machinery of the hemolymph for both parasite and mosquito-egg development. CONCLUSIONS: We conclude that the determinants of malaria-parasite development in Anopheles include components not only of systemic humoral immunity but also of intracellular, local epithelial reactions. These results provide novel mechanistic insights for understanding malaria transmission in the mosquito vector.

Actins↗

Transcriptome analysis of the pectoral fin degeneration in half-smooth tongue sole (Cynoglossus semilaevis).

Appendage degeneration is a notable morphological feature of some teleosts with specialized benthic lifestyles. The half-smooth tongue sole (Cynoglossus semilaevis) undergoes severe pectoral fin regression during metamorphosis. However, the molecular basis underlying rapid pectoral fin degeneration remains unclear. Here, we performed time-series transcriptome sequencing on pectoral fins at pre-metamorphosis, metamorphosis peak and post-metamorphosis to characterize the molecular changes associated with pectoral fin degeneration. Transcriptional dynamics and functional enrichment showed that no significant enrichment of classical apoptosis-related transcriptional pathways was detected during pectoral fin degeneration. Instead, sustained downregulation of twist1b, identified as a transcriptomic candidate, together with significant upregulation of ssh1, coupled with enrichment of lysosome and ubiquitin-proteasome system (UPS) pathways, suggested enhanced tissue remodeling during pectoral fin degeneration. Temporal expression clustering revealed heterochronic misalignment in the developmental gene expression: upstream initiator tbx5 was upregulated at early metamorphosis, while downstream maintenance signal fgf10 decreased synchronously. Distal patterning gene hoxd12a exhibited premature expression and rapid decay, losing sustained late-phase expression. Moreover, transient elevation of gli3 during metamorphosis may contribute to restricted distal fin growth. We conclude that pectoral fin degeneration in C. semilaevis is associated with heterochronic disruption of developmental signaling and extensive tissue remodeling. This study provides transcriptomic insights into pectoral fin degeneration in tongue soles and establishes a basis for future functional studies of appendage reduction in teleosts.

Animals↗

Definition of the unique human extraocular muscle allotype by expression profiling.

The extraocular muscles (EOMs) are a unique group of specialized muscles that are anatomically and physiologically distinct from other skeletal muscles. Perhaps the most striking characteristic of the EOMs is their differential sensitivity to disease. EOMs are spared in Duchenne's muscular dystrophy (DMD) despite widespread involvement of other skeletal muscles. Conversely, they are early and prominent targets in myasthenia gravis and mitochondrial myopathies. It is unclear how EOMs achieve such specialization or a differential response to diseases; however, this has been attributed to a unique, group-specific pattern of gene expression or "allotype." To begin to address these issues as well as define the human EOM allotype, we analyzed the human EOM transcriptome using oligonucleotide-based expression profiling. Three hundred thirty-eight genes were found to be differentially expressed in EOM compared with quadriceps femoris limb muscle, using a twofold cutoff. Functional characterization revealed expression patterns corresponding to known metabolic and structural properties of EOMs such as expression of EOM-specific myosin heavy chain (MYH13) and high neural, vascular, and mitochondrial content, suggesting that the profiling was sensitive and specific. Genes related to myogenesis, stem cells, and apoptosis were detected at high levels in normal human EOMs, suggesting that efficient and continuous regeneration and/or myogenesis may be a mechanism by which the EOMs remain clinically and pathologically spared in diseases such as DMD. Taken together, this study provides insight into how human EOMs achieve their unique structural, metabolic, and pathophysiological properties.

Adolescent↗

Comparative transcriptional profiling of Borrelia burgdorferi clinical isolates differing in capacities for hematogenous dissemination.

Borrelia burgdorferi, the etiologic agent of Lyme disease, is genetically heterogeneous. Previous studies have shown a significant association between the frequency of hematogenous dissemination in Lyme disease patients and the genotype of the infecting B. burgdorferi strain. Comparative transcriptional profiling of two representative clinical isolates with distinct genotypes (BL206 and B356) was undertaken. A total of 78 open reading frames (ORFs) had expression levels that differed significantly between the two isolates. A number of genes with potential involvement in nutrient uptake (BB0603, BBA74, BB0329, BB0330, and BBB29) have significantly higher expression levels in isolate B356. Moreover, nearly 25% of the differentially expressed genes are predicted to be localized on the cell surface, implying that these two isolates have cell surface properties that differ considerably. One of these genes, BBA74, encodes a protein of 257 amino acid residues that has been shown to possess porin activity. BBA74 transcript level was >20-fold higher in B356 than in BL206, and strain B356 contained three- to fivefold more BBA74 protein. BBA74 was disrupted by the insertion of a kanamycin resistance cassette into the coding region. The growth rates of both wild-type and mutant strains were essentially identical, and cultures reached the same final cell densities. However, the mutant strains consistently showed prolonged lags of 2 to 5 days prior to the induction of log-phase growth compared to wild-type strains. It is tempting to speculate that the absence of BBA74 interferes with the enhanced nutrient uptake that may be required for the entry of cells into log-phase growth. These studies demonstrate the value of comparative transcriptional profiling for identifying differences in the transcriptomes of B. burgdorferi clinical isolates that may provide clues to pathogenesis. The 78 ORFs identified here are a good starting point for the investigation of factors involved in the hematogenous dissemination of B. burgdorferi.

Alleles↗

Integrative Multiomics and Drug Sensitivity Profiling Reveal Potential Biomarkers and Therapeutic Strategies in Pediatric Solid Tumors.

UNLABELLED: Cure rates for childhood malignancies using established therapy protocols have increased to an average of 80% but have reached a plateau. Moreover, survival rates are particularly low for some pediatric tumors-such as high-risk group 3 medulloblastomas, osteosarcomas, Ewing sarcomas, high-risk neuroblastomas, and high-grade gliomas-and dismal for patients with relapsed malignancies. A functional drug response profiling platform for pediatric solid and brain tumors has been established within the INFORM program to identify patient-specific vulnerabilities and biomarkers and to unravel molecular mechanisms associated with drug response profiles for clinical translation. In this study, we performed a multiomics analysis using drug sensitivity profiles, as well as genomic and transcriptomic data, of 81 pediatric solid tumor samples. The integrative analysis suggested two multiomics signatures associated with drug sensitivity. One signature distinguished neuroblastoma samples with sensitivity to navitoclax, a BCL2 family inhibitor. A second signature was specific to a subset of Wilms tumors harboring the SIX1 (Q177R) hotspot mutation that displayed high expression of MGAM, PTPN14, STAT4, and KDM2B and high sensitivity to MEK inhibitors. A patient-specific causal interaction network analysis suggested possible molecular interactions between MEK inhibitors and the SIX1 mutation in Wilms tumor samples. In conclusion, the integration of drug sensitivity profiling and multiomics data revealed potential biomarkers that may be associated with drug sensitivity in pediatric solid tumors. Patient-specific causal interaction network analysis further elucidated the interaction between inhibitors and signature biomarkers, providing insights that may inform clinical translation. SIGNIFICANCE: The combination of multiomics analysis and drug sensitivity profiling identified two signatures related to drug sensitivity in pediatric solid tumors, contributing to the advancement of functional precision medicine and personalized treatment strategies. This article is part of a special series: Driving Cancer Discoveries with Computational Research, Data Science, and Machine Learning/AI .

Humans↗

Generating correlated data for omics simulation.

Simulation of realistic omics data is a key input for benchmarking studies that help users obtain optimal computational pipelines. Omics data involves large numbers of measured features on each sample and these measures are generally correlated with each other. However, simulation too often ignores these correlations, perhaps due to computational and statistical hurdles of doing so. To alleviate this, we describe three approaches for generating omics-scale data with correlated measures which mimic real datasets. These approaches are all based on a Gaussian copula approach with a covariance matrix that decomposes into a diagonal part and a low-rank part. This decomposition allows for extremely efficient simulation, overcoming a hurdle for adoption of past methods. We use these approaches to demonstrate the importance of including correlation in two benchmarking applications. First, we show that variance of results from the popular DESeq2 method increases when dependence is included. Second, we demonstrate that CYCLOPS, a method for inferring circadian time of collection from transcriptomics, improves in performance when given gene-gene dependencies in some circumstances. We provide an R package, dependentsimr, that has efficient implementations of these methods and can generate dependent data with arbitrary marginal distributions, including discrete (binary, ordered categorical, Poisson, negative binomial), continuous (normal), or with an empirical distribution.

Computer Simulation↗

SpatioMark: quantifying the impact of spatial proximity on cell phenotype.

MOTIVATION: As research advances in spatially resolving the biological archetype of various diseases, technologies that capture the spatial relationships between cells are demonstrating increasing value. Whilst there are an increasing number of analytical methods being developed to identify the complex web of interactions between cells, the downstream impacts of these cell-cell relationships are under explored. RESULTS: We present SpatioMark, a statistical framework that simplifies the assessment of gene or protein expression changes within a cell type that are associated with the spatial proximity to other cell types. We demonstrate its performance across spatial proteomics and transcriptomics datasets. We link identified relationships with differences in patient survival. We highlight key challenges in identifying changes in molecular markers associated with the localization of cells. We propose correction strategies that reduce artefact-induced relationships. AVAILABILITY AND IMPLEMENTATION: SpatioMark is implemented in the Statial R package on Bioconductor: https://bioconductor.org/packages/release/bioc/html/Statial.html.

Humans↗

Gene expression profiling using a novel method: amplified differential gene expression (ADGE).

Amplified differential gene expression (ADGE) is a novel technique, designed to profile gene expression of the whole transcriptome or to compare expression of a set of genes between two samples. ADGE employs hybridization to quadratically amplify the ratio of an expressed gene between control and tester samples before displaying. The subtle structures of adapters and primers are designed for displaying the amplified ratio of an expressed gene between two samples. Four selective nucleotides at the 3' end of primers are used to increase PCR efficiency for targeted molecules and to improve detection of PCR products. Double PCR with the same pair of primers expands the detection range, especially for genes of low abundance. Integration of these steps makes ADGE sensitive and accurate. Application to drug resistant human tumor cell lines showed that ADGE accurately profiled expression levels for induced, repressed or unchanged genes. The qualitative expression patterns for ADGE were verified with RT-PCR.

DNA Primers↗

Activity profiling of papain-like cysteine proteases in plants.

Transcriptomic and proteomic technologies are generating a wealth of data that are frequently used by scientists to predict the function of proteins based on their expression or presence. However, activity of many proteins, such as transcription factors, kinases, and proteases, depends on posttranslational modifications that frequently are not detected by these technologies. Therefore, to monitor activity of proteases rather than their abundance, we introduce protease activity profiling in plants. This technology is based on the use of biotinylated, irreversible protease inhibitors that react with active proteases in a mechanism-based manner. Using a biotinylated derivative of the Cys protease inhibitor E-64, we display simultaneous activities of many papain-like Cys proteases in extracts from various tissues and from different plant species. Labeling is pH dependent, stimulated with reducing agents, and inhibited specifically by Cys protease inhibitors but not by inhibitors of other protease classes. Using one-step affinity capture of biotinylated proteases followed by sequencing mass spectrometry, we identified proteases that include xylem-specific XCP2, desiccation-induced RD21, and cathepsin B- and aleurain-like proteases. Together, these results demonstrate that this technology can identify differentially activated proteases and/or characterize the activity of a particular protease within complex mixtures.

Amino Acid Sequence↗

Transcriptomics and proteomics: tools for optimising phytoremediation activities.

Negligent industrial development has greatly contributed to environmental pollution through the contamination of water and soil by xenobiotic organic chemicals Remedial strategies to deal with chemical pollution require reliable methods to identify and monitor contamination, as well as effective procedures to attenuate or to eliminate the pollutant. In the food chain, plants are ideally placed as early bio-indicators of environmental pollution as they experience and respond to environmental toxicants sooner than organisms at higher trophic levels. Furthermore, some plants are capable of detoxifying anthropogenic chemicals by metabolic transformation and could prove useful for the remediation of contaminated water and soil: so-called phytoremediation. So far research technologies aimed at developing plants for bio-indication/bio-monitoring and for remediation have largely relied on standardised chemical and biochemical procedures to evaluate phytotoxicity, metabolic fate and persistence of organic pollutants in plants. The next stage in the evolution of these plant-based technologies is the improvement and optimisation of any innate phytoremediation activities identified in selected plants. In general, uptake followed by metabolism and compartmentation is responsible for the detoxification of organic xenobiotics in plants. These are complex cellular systems that may be organised in well-defined pathways and are often controlled by large families of genes. In order to elucidate complex traits such as detoxification, an emerging idea is to make use of global approaches such as the new "omic" technologies to identify molecular changes in plant tissues exposed to specific organic xenobiotics. From expression profiles at the messenger RNA level, transcriptomics permit the identification of function-related gene clusters and at the protein level proteomics provide information on where, when and at what level specific proteins accumulate. We conclude that these global approaches may be a useful way of widening screening capability to identify appropriate molecular markers that can be used to improve detoxification activity.

Arabidopsis↗