Authentication and identification markers for medicinal plants: I Aristolochia bracteolata

<p class="abstract"><strong>Background:</strong> Aristolochiaceae is a unique plant family that contains aristolochic acids (AAs), with around 600 species.</p><p class="abstract"><strong>Methods:</strong> The entire chloroplast genome of <em>Aristolochia bracteolata</em> was sequenced in this work, and fourteen chloroplast (cp) genomes were retrieved from the NCBI database. </p><p class="abstract"><strong>Results:</strong> We also analyzed six types of microsatellite markers among these species and found some different markers for each species. A molecular phylogeny based on 7 barcode regions i.e. <em>matK,</em> <em>atpF</em> to <em>atpH</em>, <em>psbK</em> to <em>psbI</em>, <em>rbcL, rpoB, rpoC2</em> and <em>rpoC1</em> is proposed for <em>Aristolochia </em>and 16 species from Piperales, <em>Arabidopsis thaliana</em> is taken as an outgroup. Phylogenetic relationships using concatenated protein-coding genes from Chloroplast genomes of Piperales using the maximum likelihood method is also discussed.</p><p class="abstract"><strong>Conclusions:</strong> In the present study we are providing some unique markers<strong> </strong>and phylogenetic relationships among Piperales members which will help in identification, authentication, to prevent adulteration and further investigation of these medicinal plants.</p>

Single Cell Transcriptomic Analysis of Spinal Dmrt3 Neurons in Zebrafish and Mouse Identifies Distinct Subtypes and Reveal Novel Subpopulations Within the dI6 Domain

The spinal locomotor network is frequently used for studies into how neuronal circuits are formed and how cellular activity shape behavioral patterns. A population of dI6 interneurons, marked by the Doublesex and mab-3 related transcription factor 3 (Dmrt3), has been shown to participate in the coordination of locomotion and gaits in horses, mice and zebrafish. Analyses of Dmrt3 neurons based on morphology, functionality and the expression of transcription factors have identified different subtypes. Here we analyzed the transcriptomes of individual cells belonging to the Dmrt3 lineage from zebrafish and mice to unravel the molecular code that underlies their subfunctionalization. Indeed, clustering of Dmrt3 neurons based on their gene expression verified known subtypes and revealed novel populations expressing unique markers. Differences in birth order, differential expression of axon guidance genes, neurotransmitters, and their receptors, as well as genes affecting electrophysiological properties, were identified as factors likely underlying diversity. In addition, the comparison between fish and mice populations offers insights into the evolutionary driven subspecialization concomitant with the emergence of limbed locomotion.

Single-Larva RNA Sequencing Identifies Markers of Copper Toxicity and Exposure in Early Mytilus californianus Larvae

One of the challenges facing efforts to generate molecular biomarkers for toxins is distinguishing between markers that are indicative of exposure and markers that provide evidence of the effects of toxicity. Phenotypic anchoring provides an approach to help segregate markers into these categories based on some phenotypic index of toxicity. Here we leveraged the mussel embryo-larval toxicity assay in which toxicity is estimated by the fraction of larvae that exhibit an abnormal morphology, to isolate subsets of larvae that were abnormal and thus showed evidence of copper-toxicity, versus others that while exposed to copper exhibited normal morphology. Mussel larvae reared under control conditions or in the presence of increasing levels of copper (3–15 μg/L Cu2+) were physically sorted according to whether their morphology was normal or abnormal, and then profiled using RNAseq. Supervised differential expression analysis identified sets of genes whose differential expression was specific to the pools of abnormal larvae versus normal larvae, providing putative markers of copper toxicity versus exposure. Markers of copper exposure and copper-induced abnormality were involved in many of the same pathways, including development, shell formation, cell adhesion, and oxidative stress, yet unique markers were detected in each gene set. Markers of effect appeared to be more resolving between phenotypes at the lower copper concentration, while markers of exposure were informative at both copper concentrations.

Probing the Metabolic Landscape of Plant Vascular Bundles by Infrared Fingerprint Analysis, Imaging and Mass Spectrometry

Fingerprint analysis is a common technique in forensic and criminal investigations. Similar techniques exist in the field of infrared spectroscopy to identify biomolecules according to their characteristic spectral fingerprint features. These unique markers are located in a wavenumber range from 1800 to 600 cm−1 in the mid infrared region. Here, a novel bioanalytical concept of correlating these spectral features with corresponding mass spectrometry datasets to unravel metabolic clusters within complex plant tissues was applied. As proof of concept, vascular bundles of oilseed rape (Brassica napus) were investigated, one of the most important and widely cultivated temperate zone oilseed crops. The link between mass spectrometry data and spectral data identified features that co-aligned within both datasets. Regions of origin were then detected by searching for these features in hyperspectral images of plant tissues. This approach, based on co-alignment and co-localization, finally enabled the detection of eight distinct metabolic clusters, reflecting functional and structural arrangements within the vascular bundle. The proposed analytical concept may assist future synergistic research approaches and may lead to biotechnological innovations with regard to crop yield and sustainability.

A Portrait of Intratumoral Genomic and Transcriptomic Heterogeneity at Single-Cell Level in Colorectal Cancer

In the study of cancer, omics technologies are supporting the transition from traditional clinical approaches to precision medicine. Intra-tumoral heterogeneity (ITH) is detectable within a single tumor in which cancer cell subpopulations with different genome features coexist in a patient in different tumor areas or may evolve/differ over time. Colorectal carcinoma (CRC) is characterized by heterogeneous features involving genomic, epigenomic, and transcriptomic alterations. The study of ITH is a promising new frontier to lay the foundation towards successful CRC diagnosis and treatment. Genome and transcriptome sequencing together with editing technologies are revolutionizing biomedical research, representing the most promising tools for overcoming unmet clinical and research challenges. Rapid advances in both bulk and single-cell next-generation sequencing (NGS) are identifying primary and metastatic intratumoral genomic and transcriptional heterogeneity. They provide critical insight in the origin and spatiotemporal evolution of genomic clones responsible for early and late therapeutic resistance and relapse. Single-cell technologies can be used to define subpopulations within a known cell type by searching for differential gene expression within the cell population of interest and/or effectively isolating signal from rare cell populations that would not be detectable by other methods. Each single-cell sequencing analysis is driven by clustering of cells based on their differentially expressed genes. Genes that drive clustering can be used as unique markers for a specific cell population. In this review we analyzed, starting from published data, the possible achievement of a transition from clinical CRC research to precision medicine with an emphasis on new single-cell based techniques; at the same time, we focused on all approaches and issues related to this promising technology. This transition might enable noninvasive screening for early diagnosis, individualized prediction of therapeutic response, and discovery of additional novel drug targets.

Using the T Cell Receptor as a Biomarker in Type 1 Diabetes

T cell receptors (TCRs) are unique markers that define antigen specificity for a given T cell. With the evolution of sequencing and computational analysis technologies, TCRs are now prime candidates for the development of next-generation non-cell based T cell biomarkers, which provide a surrogate measure to assess the presence of antigen-specific T cells. Type 1 diabetes (T1D), the immune-mediated form of diabetes, is a prototypical organ specific autoimmune disease in which T cells play a pivotal role in targeting pancreatic insulin-producing beta cells. While the disease is now predictable by measuring autoantibodies in the peripheral blood directed to beta cell proteins, there is an urgent need to develop T cell markers that recapitulate T cell activity in the pancreas and can be a measure of disease activity. This review focuses on the potential and challenges of developing TCR biomarkers for T1D. We summarize current knowledge about TCR repertoires and clonotypes specific for T1D and discuss challenges that are unique for autoimmune diabetes. Ultimately, the integration of large TCR datasets produced from individuals with and without T1D along with computational ‘big data’ analysis will facilitate the development of TCRs as potentially powerful biomarkers in the development of T1D.

The Cellular and Molecular Basis of Sour Taste

Sour taste, the taste of acids, is one of the most enigmatic of the five basic taste qualities; its function is unclear and its receptor was until recently unknown. Sour tastes are transduced in taste buds on the tongue and palate epithelium by a subset of taste receptor cells, known as type III cells. Type III cells express a number of unique markers, including the PKD2L1 gene, which allow for their identification and manipulation. These cells respond to acid stimuli with action potentials and release neurotransmitters onto afferent nerve fibers, with cell bodies in geniculate and petrosal ganglia. Here, we review classical studies of sour taste leading up to the identification of the sour receptor as the proton channel, OTOP1. Expected final online publication date for the Annual Review of Physiology, Volume 84 is February 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Mesenchymal stem cells from biology to therapy

Mesenchymal stem cells are as fascinating as they are enigmatic. They appear capable of performing a wide array of functions that cross skeletal biology, immunology and haematology. As therapeutics, mesenchymal stem cells or even just their secreted products may be used to regenerate tissue lost through injury or disease and suppress damaging immune reactions. However, these cells lack unique markers and are hard to identify and isolate as pure cell populations. They are often grown in laboratories using basic and undefined culture conditions. We cannot even agree on their name. While mesenchymal stem cells may lack the developmental understanding and defined differentiation hierarchies of their more illustrious stem cell cousins, they offer a compelling scientific challenge. In depth understanding of mesenchymal stem cell biology will enable us to exploit fully one of the most clinically valuable cell sources.

Structure of Author’s Concept «Witch» (a Case Study of J. K. Rowling’s Novel «Harry Potter and the Goblet of Fire»)

This article describes the core structure of one of the most important concepts in the series of novels by J. K. Rowling «Harry Potter», the concept «witch» and its corresponding concept in the Russian language, the concept «ведьма». Both of these concepts are extremely important for the majority of fantasy pieces of literature, they contribute to the authentic worldview. The model of the author’s concept «witch» is conveyed with the help of the analyses of verbalization of the concept in the original text. The invariant features of the concept are identified by comparing the models of traditional and author’s concepts, as well as the unique markers of the author’s concept. The most common transformations and techniques used by translators are highlighted through the comparative analyses of two variants of translation of the same novel. This also shows the ways that were used to verbalize the English concepts in Russian translation.

Autonomous Flight Trajectory Control System for Drones in Smart City Traffic Management

With the exponential growth of numerous drone operations ranging from infrastructure monitoring to even package delivery services, the integration of UAS in the smart city transportation systems is an actual task that requires radically new, sustainable (safe, secure, with minimum environmental impact and life cycle cost) solutions. The primary objective of this proposed option is the definition of routes as desired and commanded trajectories and their autonomous execution. The airspace structure and fixed routes are given in the global GPS reference system with supporting GIS mapping. The concept application requires a series of further studies and solutions as drone trajectory (or corridor) following by an autonomous trajectory tracking control system, coupled with autonomous conflict detection, resolution, safe drone following, and formation flight options. The second part of the paper introduces such possible models and shows some results of their verification tests. Drones will be connected with the agency, designed trajectories to support them with factual information on trajectories and corridors. While the agency will use trajectory elements to design fixed or desired trajectories, drones may use the conventional GPS, infrared, acoustic, and visual sensors for positioning and advanced navigation. The accuracy can be improved by unique markers integrated into the infrastructure.