The molecular interactions between a pest and its host plant are the consequence of an evolutionary arms race based on the perception of the phytophagous arthropod by the plant and the different strategies adopted by the pest to overcome plant triggered defenses. The complexity and the different levels of these interactions make it difficult to get a wide knowledge of the whole process. Extensive research in model species is an accurate way to progressively move forward in this direction. The two-spotted spider mite, Tetranychus urticae Koch has become a model species for phytophagous mites due to the development of a great number of genetic tools and a high-quality genome sequence. This review is an update of the current state of the art in the molecular interactions between the generalist pest T. urticae and its host plants. The knowledge of the physical and chemical constitutive defenses of the plant and the mechanisms involved in the induction of plant defenses are summarized. The molecular events produced from plant perception to the synthesis of defense compounds are detailed, with a special focus on the key steps that are little or totally uncovered by previous research.

Transcriptional plant responses are an important aspect of herbivore oviposition studies. However, most of our current knowledge is derived from studies using Lepidopteran models, where egg-laying and feeding are separate events in time. Little is known regarding plant response to pests where females feed and oviposit simultaneously. The present study characterized oviposition-induced transcriptomic response of Arabidopsis to Tetranychus urticae egg extracts. Transcriptional evidence indicates that early events in plant response to the egg extract involve responses typical to biotic stresses, which include the alteration in the levels of Ca2+ and ROS, the modification of pathways regulated by the phytohormones jasmonic acid and ethylene, and the production of volatiles and glucosinolates as defence mechanisms. These molecular changes affect female fertility, which was significantly reduced when mites fed on plants pre-exposed to the egg extract. However, longer periods of plant exposure to egg extract cause changes in the transcriptional response of the plant reveal a trend to a decrease in the activation of the defensive response. This alteration correlated with a shift at 72 h of exposition in the effect of the mite feeding. At that point, plants become more susceptible and suffer higher damage when challenged by the mite.

Background The model species Tetranychus urticae produces important plant injury and economic losses in the field. The current accepted method for the quantification of the spider mite damage in Arabidopsis whole rosettes is time consuming and entails a bottleneck for large-scale studies such as mutant screening or quantitative genetic analyses. Here, we describe an improved version of the existing method by designing an automatic protocol. The accuracy, precision, reproducibility and concordance of the new enhanced approach are validated in two Arabidopsis accessions with opposite damage phenotypes. Results are compared to the currently available manual method. Results Image acquisition experiments revealed that the automatic settings plus 10 values of brightness and the black background are the optimal conditions for a specific recognition of spider mite damage by software programs. Among the different tested methods, the Ilastik-Fiji tandem based on machine learning was the best procedure able to quantify the damage maintaining the differential range of damage between accessions. In addition, the Ilastik-Fiji tandem method showed the lowest variability within a set of conditions and the highest stability under different lighting or background surroundings. Bland-Altman concordance results pointed out a negative value for Ilastik-Fiji, which implies a minor estimation of the damage when compared to the manual standard method. Conclusions The novel approach using Ilastik and Fiji programs entails a great improvement for the quantification of the specific spider mite damage in Arabidopsis whole rosettes. The automation of the proposed method based on interactive machine learning eliminates the subjectivity and inter-rater-variability of the previous manual protocol. Besides, this method offers a robust tool for time saving and to avoid the damage overestimation observed with other methods.

Herbivore oviposition produces all sorts of responses in plants, involving wide and complex genetic rearrangements. Many transcriptomic studies have been performed to understand this interaction, producing a bulk of transcriptomic data. However, the use of many transcriptomic techniques across the years, the lack of comparable transcriptomic context at the time of publication, and the use of outdated databases are limitations to understand this biological process. The current analysis intends to retrieve oviposition studies and process them with up-to-date techniques and updated databases. To reduce heterogeneities, the same processing techniques were applied, and Arabidopsis was selected to avoid divergencies on plant taxa stress response strategies. By doing so, we intended to understand the major mechanisms and regulatory processes linked to oviposition response. Differentially expressed gene (DEG) identification and co-expression network-based analyses were the main tools to achieve this goal. Two microarray studies and three RNA-seq analyses passed the screening criteria. The collected data pertained to the lepidopteran Pieris brassicae and the mite Tetranychus urticae, and covered a timeline from 3 to 144 h. Among the 18, 221 DEGs found, 15, 406 were exclusive of P. brassicae (72 h) and 801 were exclusive for the rest of the experiments. Excluding P. brassicae (72 h), shared genes on the rest of the experiments were twice the unique genes, indicating common response mechanisms were predominant. Enrichment analyses indicated that shared processes were circumscribed to earlier time points, and after 24 h, the divergences escalated. The response was characterized by patterns of time-dependent waves of unique processes. P. brassicae oviposition induced a rich response that shared functions across time points, while T. urticae eggs triggered less but more diverse time-dependent functions. The main processes altered were associated with hormonal cascades [e.g., salicilic acid (SA) and jasmonic acid (JA)], defense [reactive oxygen species (ROS) and glucosinolates], cell wall rearrangements, abiotic stress responses, and energy metabolism. Key gene drivers of the identified processes were also identified and presented. The current results enrich and clarify the information regarding the molecular behavior of the plant in response to oviposition by herbivores. This information is valuable for multiple stress response engineering tools, among other applications.