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You are an expert at identifying data availability statements in scientific text. A data availability statement describes where research data can be found or how it can be accessed.<|eot_id|><|start_header_id|>user<|end_header_id|>

Determine if the following text contains a data availability statement. Answer with 'yes' or 'no'.

Text: To echo this last point, one of the main challenges of metabolomics in plant pathology is distinguishing plant and microbial metabolomes [80]. Metabolites, most particularly primary compounds, are often ubiquitous in the diverse plant, microbial and animal organisms, or exchanged between the host and pathogens, as signals or metabolic responses. In pathological studies (Figure 1), plants and microbes are jointly incubated, but the pathogens are rarely removed before metabolite extraction, thereby mixing metabolomes of different origins. This probably seems to be of minor importance for other omics, such as transcriptomics and proteomics, which exploit species-specific databases. However, metabolomics suffers from cross-contamination of the host and non-host metabolites; therefore, it is often difficult to draw precise conclusions as to the origin of the metabolic variations found. Whilst one can search **data** for metabolites of non-plant origin, for example, arachidonic acid with respect to fungal pathogens, one cannot assume that their absence suggests that metabolites of fungal origin are not being detected. Implementing stable isotope labelling of microbes could address this pressing concern. A recent metabolomics study of the early stage of plant cell-microbe interactions employed an incubation method of 13 C-and 15 N-labelled (98%) Pst DC3000 with Arabidopsis cells, followed by a washing step to remove the excess bacterial cells [169]. Subsequently, "light" plant metabolites were analyzed by targeted LC-MS, highlighting an infection reprogramming of plant signaling and primary metabolic pathways, including carbohydrates, nucleotides, and amino and organic acids. Alternatively, uniformly 13 C-and 15 N-labelled plants can be prepared, which will offer an accurate tool for metabolomic analysis under biotic stress conditions [170]. The growing interest in isotopically labelled biological material coincides with the development of additional analytical tools, such as NMR and high-throughput GC-and LC-HRMS, which allow the discrimination between native and labelled metabolites ( Figure 3). It is conceivable that elegant studies of this type will be carried out less sporadically, to help clarify the origin of changes in the host and pathogen metabolome. In summary, future prospects that will greatly contribute to the success of metabolomics in the study of plant immunity will include (i) increasing the capacity to chromatopgraphically resolve and annotate plant and pathogen metabolomes, (ii) new tools and approaches to analyze the metabolome at the subcellular level, and (iii) the development and implementation of modelling, to predict and/or calculate the dynamics of metabolic variations.<|eot_id|><|start_header_id|>assistant<|end_header_id|>

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