Analyzing cadmium-phytochelatin2 complexes in plant using terahertz and circular dichroism information

Unlocking protein-protein interactions in plants: a comprehensive review of established and emerging techniques

Protein-protein interactions orchestrate plant development and serve as crucial elements for cellular and environmental communication. Understanding these interactions offers a gateway to unravel complex protein networks that will allow a better understanding of nature. Methods for the characterization of protein-protein interactions have been around over 30 years, yet the complexity of some of these interactions has fueled the development of new techniques that provide a better understanding of the underlying dynamics. In many cases, the application of these techniques is limited by the nature of the available sample. While some methods require an in vivo set-up, others solely depend on protein sequences to study protein-protein interactions via an in silico set-up. The vast number of techniques available to date calls for a way to select the appropriate tools for the study of specific interactions. Here, we classify widely spread tools and new emerging techniques for the characterization of protein-protein interactions based on sample requirements while providing insights into the information that they can potentially deliver. We provide a comprehensive overview of commonly used techniques and elaborate on the most recent developments, showcasing their implementation in plant research.

Concise Cascade Methods for Transgenic Rice Seed Discrimination using Spectral Phenotyping

Currently, the presence of genetically modified (GM) organisms in agro-food markets is strictly regulated by enacted legislation worldwide. It is essential to ensure the traceability of these transgenic products for food safety, consumer choice, environmental monitoring, market integrity, and scientific research. However, detecting the existence of GM organisms involves a combination of complex, time-consuming, and labor-intensive techniques requiring high-level professional skills. In this paper, a concise and rapid pipeline method to identify transgenic rice seeds was proposed on the basis of spectral imaging technologies and the deep learning approach. The composition of metabolome across 3 rice seed lines containing the cry1Ab/cry1Ac gene was compared and studied, substantiating the intrinsic variability induced by these GM traits. Results showed that near-infrared and terahertz spectra from different genotypes could reveal the regularity of GM metabolic variation. The established cascade deep learning model divided GM discrimination into 2 phases including variety classification and GM status identification. It could be found that terahertz absorption spectra contained more valuable features and achieved the highest accuracy of 97.04% for variety classification and 99.71% for GM status identification. Moreover, a modified guided backpropagation algorithm was proposed to select the task-specific characteristic wavelengths for further reducing the redundancy of the original spectra. The experimental validation of the cascade discriminant method in conjunction with spectroscopy confirmed its viability, simplicity, and effectiveness as a valuable tool for the detection of GM rice seeds. This approach also demonstrated its great potential in distilling crucial features for expedited transgenic risk assessment.

Phytochelatins: Sulfur-Containing Metal(loid)-Chelating Ligands in Plants

Phytochelatins (PCs) are small cysteine-rich peptides capable of binding metal(loid)s via SH-groups. Although the biosynthesis of PCs can be induced in vivo by various metal(loid)s, PCs are mainly involved in the detoxification of cadmium and arsenic (III), as well as mercury, zinc, lead, and copper ions, which have high affinities for S-containing ligands. The present review provides a comprehensive account of the recent data on PC biosynthesis, structure, and role in metal(loid) transport and sequestration in the vacuoles of plant cells. A comparative analysis of PC accumulation in hyperaccumulator plants, which accumulate metal(loid)s in their shoots, and in the excluders, which accumulate metal(loid)s in their roots, investigates the question of whether the endogenous PC concentration determines a plant's tolerance to metal(loid)s. Summarizing the available data, it can be concluded that PCs are not involved in metal(loid) hyperaccumulation machinery, though they play a key role in metal(loid) homeostasis. Unraveling the physiological role of metal(loid)-binding ligands is a fundamental problem of modern molecular biology, plant physiology, ionomics, and toxicology, and is important for the development of technologies used in phytoremediation, biofortification, and phytomining.

Vibrational Spectroscopy Combined with Chemometrics in Authentication of Functional Foods

Many foods have both edible and medical importance and are appreciated as functional foods, preventing diseases. However, due to unscrupulous vendors and imperfect market supervision mechanisms, curative foods are prone to adulteration or some other events that harm the interests of consumers. However, traditional analytical methods are unsuitable and expensive for a broad and complex application. Therefore, people urgently need a fast, efficient, and accurate detection method to protect self-interests. Recently, the study of target samples by vibration spectrum shows strong qualitative and quantitative ability. The model established by platform technology combined with the stoichiometric analysis method can obtain better parameters, which it has good robustness and can detect functional food efficiently, quickly and nondestructive. The review compared and prospect five different vibrational spectroscopic techniques (near-infrared, Fourier transform infrared, Raman, hyperspectral imaging spectroscopy and Terahertz spectroscopy). In order to better solve some of the actual situations faced by certification, we explore and through relevant research and investigation to appropriately highlight the applicability and importance of technology combined with chemometrics in functional food authentication. There are four categories of authentication discussed: functional food authenticated in source, processing method, fraud and ingredient ratio. This paper provides an innovative process for the authentication of functional food, which has a meaningful reference value for future review or scientific research of relevant departments.

Structure analysis and non-invasive detection of cadmium-phytochelatin2 complexes in plant by deep learning Raman spectrum

Plants synthesize phytochelatins to chelate in vivo toxic heavy metal ions and produce nontoxic complexes for tolerating the stress. Detection of the complexes would simplify the identification of high phytoremediation cultivars, as well as assessment of plant food for safe consumption. Thus, a confocal Raman spectroscopy combined with density functional theory and deep learning was used for characterizing phytochelatin2 (PC₂), and Cd-PC₂ mixtures. Results showed the PC₂ chelate Cd²⁺ in a 2:1 ratio to produce Cd(PC₂)₂; Cd-S bonds of the Cd(PC₂)₂ have signature Raman vibrations at 305 and 610 cm^-1 which are the most distinctive spectral signatures for varieties of Cd-PCs complexes. The PC₂ was used as a natural probe to stabilize the chemical status of Cd, and to enrich and magnify Raman signature of the trace Cd for deep learning models which enabled condition of the Cd(PC₂)₂ in pak choi leaf to be visualized, quantified, and classified by directly using raw spectra of the leaf. This study provides a general protocol by using Raman information for structure analysis and non-invasive detection of heavy metal-PCs complexes in plants and provides a novel idea for simplifying identification of high phytoremediation cultivars, as well as assessment of heavy metal related food safeties.