Quantification Of Transcripts Research Articles

Reference gene selection for qRT-PCR analysis in the shoots and roots of Camellia sinensis var. sinensis under nutritional stresses

Quantitative real-time polymerase chain reaction (qRT-PCR) is a useful way to evaluate gene expression level, in which the selection of internal references needs to be addressed firstly. However, the stably expressed reference genes in tea plants (Camellia sinensis var. sinensis) under different nutrient deficiency has not been reported. In this study, seven candidate reference genes (i.e., ACTIN7, EF-1α, eIF-4α, GAPDH, PP2A, TBP and TIP41) were employed to evaluate their expression stability using three algorithmic programs (i.e., geNorm, NormFinder and BestKeeper) under six kinds of nutrient deficiency conditions [i.e., ammonium nitrogen (-NH4+-N), nitrate nitrogen (-NO3−-N), phosphorus (-P), potassium (-K), calcium (-Ca) and magnesium (-Mg)] in C. sinensis shoots and roots. The results showed that (1) the combinations of PP2A and ACTIN were stably expressed in shoots under -NH4+-N and EF-1α combined with PP2A and TBP were stably expressed in -NH4+-N roots or -P shoots; (2) the combinations of ACTIN and EF-1α or ACTIN and TBP were stable in shoots and roots under -NO3−-N; (3) TBP combined with EF-1α and TIP41 was stably expressed in -P roots-Ca roots; (4) eIF-4α and ACTIN exhibited stable expression in -K shoots and the combination of EF-1α and TIP41 was stable in -K roots; (5) GAPDH and EF-1α or EF-1α and eIF-4α were stably expressed in -Ca or -Mg shoots and TIP41 combined with ACTIN and eIF-4α was stably expressed in -Mg roots. Moreover, six nutrient deficiency responsive genes (i.e., CsAMT1;2, CsNRT2;6, CsPT4, CsKT8, CsCTA11 and CsMGT1) were chosen to validate the suitability of the selected reference genes, and the expression levels of these target genes showed significant difference when using the most stable single gene (or combination of genes) and the least stable gene for normalization. These results provide guidelines and facilitate the quantification of gene transcription in C. sinensis shoots and roots under macro- and medium-element deficient conditions.

Abstract A005: Androgen receptor variants mRNA absolute quantification in prostate cancer cell models

Abstract Background: Patients treated with Androgen Deprivation Therapy (ADT) have been shown to increase the expression of constitutively active Androgen Receptor (AR) splice variants (AR-Vs). These splice variants lack the ligand binding domain at the C-terminus of AR, required for binding to antiandrogen therapies. AR-V7 has also been correlated to the development and progression of castration resistant prostate cancer (CRPC). As not all circulating tumor cells (CTCs) contain AR-V7, we hypothesized that other AR-Vs are involved in the mechanism of resistance to ADT commonly seen in CRPC. To test this, we developed an mRNA quantitative assay targeting AR-Vs and then correlated our results with a targeted mass spectrometry (MS) based protein assay. This work will provide a feasible quantification of AR-V transcripts and that may provide a stratification for predicted responses to ADT treatment in patients that could be useful to clinicians. Methods: The absolute copy number of total AR, AR-V2, AR-V7, AR-V12, and AR-V23 were determined in eight different PCa cell lines and 48 patient derived xenografts (PDXs) using qRT-PCR assays. We performed siRNA targeting of these variants to evaluate primer specificity by evaluating knockdown efficiencies. These results will be correlated to targeted MS quantification of AR-Vs in each cell model. Results: We found that the most highly expressed variants in PCa cell lines were AR-V7 and AR-V12. In the LuCaP PDX model, AR-V12 was shown to have the highest expression of the AR-Vs tested. Specificity of AR-V knockdown was tested using AD-1 (which only expresses the full- length AR transcript) and R1-D567 (which only expresses AR-V567es, an AR-V12-like variant) cell lines. Conclusions: We were able to determine the landscape of AR-V mRNA expression in eight PCa cell lines and in 48 PDX tumor samples. This data will be correlated to protein expression currently being analyzed using a targeted MS method developed in our lab. Our work will be useful to help clinicians stratify PCa patients based on their AR-V expression profiles. This will establish a prognostic biomarker program that measures AR-V proteins in real time from clinical biopsy tissues, circulating tumor cells, or exosomes and informs the clinician on which course of treatment may be effective for each patient. Establishing a CRPC biomarker other than AR-V7 that can help explain the AR-V7 negative CRPC patients could eventually improve clinical application and predictive treatment outcomes. Citation Format: Gabrianne Larson, Zoi Sychev, Stephen Plymate, Eva Corey, Justin M. Drake. Androgen receptor variants mRNA absolute quantification in prostate cancer cell models [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr A005.

IsoTools: a flexible workflow for long-read transcriptome sequencing analysis.

Long-read transcriptome sequencing (LRTS) has the potential to enhance our understanding of alternative splicing and the complexity of this process requires the use of versatile computational tools, with the ability to accommodate various stages of the workflow with maximum flexibility. We introduce IsoTools, a Python-based LRTS analysis framework that offers a wide range of functionality for transcriptome reconstruction and quantification of transcripts. Furthermore, we integrate a graph-based method for identifying alternative splicing events and a statistical approach based on the beta-binomial distribution for detecting differential events. To demonstrate the effectiveness of our methods, we applied IsoTools to PacBio LRTS data of human hepatocytes treated with the histone deacetylase inhibitor valproic acid. Our results indicate that LRTS can provide valuable insights into alternative splicing, particularly in terms of complex and differential splicing patterns, in comparison to short-read RNA-seq. IsoTools is available on GitHub and PyPI, and its documentation, including tutorials, CLI, and API references, can be found at https://isotools.readthedocs.io/.

A multimodal atlas of tumour metabolism reveals the architecture of gene–metabolite covariation

Tumour metabolism is controlled by coordinated changes in metabolite abundance and gene expression, but simultaneous quantification of metabolites and transcripts in primary tissue is rare. To overcome this limitation and to study gene–metabolite covariation in cancer, we assemble the Cancer Atlas of Metabolic Profiles of metabolomic and transcriptomic data from 988 tumour and control specimens spanning 11 cancer types in published and newly generated datasets. Meta-analysis of the Cancer Atlas of Metabolic Profiles reveals two classes of gene–metabolite covariation that transcend cancer types. The first corresponds to gene–metabolite pairs engaged in direct enzyme–substrate interactions, identifying putative genes controlling metabolite pool sizes. A second class of gene–metabolite covariation represents a small number of hub metabolites, including quinolinate and nicotinamide adenine dinucleotide, which correlate to many genes specifically expressed in immune cell populations. These results provide evidence that gene–metabolite covariation in cellularly heterogeneous tissue arises, in part, from both mechanistic interactions between genes and metabolites, and from remodelling of the bulk metabolome in specific immune microenvironments.

Deciphering of sulfonamide biodegradation mechanism in wetland sediments: from microbial community and individual populations to pathway and functional genes

Figuring out the comprehensive metabolic mechanism of sulfonamide antibiotics (SA) is critical to improve and optimize SA removal in the bioremediation process, but relevant studies are still lacking. Here, an approach integrating metagenomic analysis, degraders’ isolation, reverse transcriptional quantification and targeted metabolite determination was used to decipher microbial interactions and functional genes’ characteristics in SA-degrading microbial consortia enriched from wetland sediments. The SA-degrading consortia could rapidly catalyze ipso-hydroxylation and subsequent reactions of SA to achieve the complete mineralization of sulfadiazine and partial mineralization of the other two typical SA (sulfamethoxazole and sulfamethazine). Paenarthrobacter, Achromobacter, Pseudomonas and Methylobacterium were identified as the primary participants for the initial transformation of SA. Among them, Methylobacterium could metabolize the heterocyclic intermediate of sulfadiazine (2-aminopyrimidine), and the owning of sadABC genes (SA degradation genes) made Paenarthrobacter have relatively higher SA-degrading activity. Besides, the coexistence of sadABC genes and sul1 gene (SA resistance gene) gave Paenarthrobacter a dual resistance mechanism to SA. The results of reverse transcription quantification further demonstrated that the activity of sadA gene was related to the biodegradation of SA. Additionally, sadABC genes were relatively conserved in a few Microbacteriaceae and Micrococcaceae SA-degraders, but the multiple recombination events caused by densely nested transposase encoding genes resulted in the differential sequence of sadAB genes in Paenarthrobacter genome. These new findings provide valuable information for the selection and construction of engineered microbiomes.

Alpha-methyltyrosine reduces the acute cardiovascular and behavioral sequelae in a murine model of traumatic brain injury.

Increased catecholamines contribute to heightened cardiovascular reactivity and behavioral deficits after traumatic brain injury (TBI); adrenergic receptor blockade has limited success in reducing adverse sequelae of TBI. Injury-induced increases in the synthesis of catecholamines could contribute to adverse outcomes in TBI. Inhibition of catecholamine synthesis with alpha-methyltyrosine (αMT) could offer a benefit after TBI. Original research trial in mice randomized to αMT (50 mg·kg -1 ·d -1 ) or vehicle for 1 week after TBI induced by controlled cortical impact. Primary outcomes of cardiovascular reactivity and behavioral deficits were assessed after 1 week. Secondary outcomes included blood brain barrier permeability and quantification of gene transcription whose products determine intraneuronal chloride concentrations, the release of catecholamines, and activation of the sympathetic nervous system. These genes were the alpha-2 adrenergic receptor ("Adra2c"), the sodium-potassium-chloride cotransporter ("Nkcc1"), and the potassium chloride cotransporter ("Kcc2"). We also assessed the effect of TBI and αMT on the neuronal chloride/bicarbonate exchanger ("Ae3"). Traumatic brain injury-induced increases in blood pressure and cardiac reactivity were blocked by αMT. Inhibition of catecholamine synthesis decreased blood brain barrier leakage and improved behavioral outcomes after TBI. Traumatic brain injury diminished the transcription of Adra2c and enhanced expression of Nkcc1 while reducing Kcc2 transcription; αMT prevented the induction of the Nkcc1 by TBI without reversing the effects of TBI on Kcc2 expression; αMT also diminished Ae3 transcription. Traumatic brain injury acutely increases cardiovascular reactivity and induces behavioral deficits in an αMT-sensitive manner, most likely by inducing Nkcc1 gene transcription. Alpha-methyltyrosine may prove salutary in the treatment of TBI by attenuating the enhanced expression of Nkcc1, minimizing blood brain barrier leakage, and diminishing central catecholamine and sympathetic output. We also found an unreported relationship between Kcc2 and the chloride/bicarbonate exchanger, which should be considered in the design of trials planned to manipulate central intraneuronal chloride concentrations following acute brain injury.

Mapping Genetic Susceptibility to Stenosis in the Proximal Airway.

Recent translational scientific efforts in subglottic stenosis (SGS) support a disease model where epithelial alterations facilitate microbiome displacement, dysregulated immune activation, and localized fibrosis. Yet despite recent advances, the genetic basis of SGS remains poorly understood. We sought to identify candidate risk genes associated with an SGS phenotype, investigate their biological function, and identify the cell types enriched for their expression. The Online Mendelian Inheritance in Man (OMIM) database was queried for single gene variants associated with an SGS phenotype. The functional intersections and molecular roles of the identified genes were explored using pathway enrichment analysis (PEA) computational methods. Cellular localization of the candidate risk genes was measured via transcriptional quantification in an established single cell RNA sequencing (scRNA-seq) atlas of the proximal airway. Twenty genes associated with SGS phenotype were identified. PEA resulted in 24 significantly enriched terms including "cellular response to TGF-β," "epithelial-to-mesenchymal transition," and "adherens junctions." Mapping the 20 candidate risk genes to the scRNA-seq atlas found 3 (15%) genes were enriched in epithelial cells, 3 (15%) in fibroblasts, and 3 (15%) in endothelial cells. 11 (55%) genes were expressed ubiquitously among tissue types. Interestingly, immune cells were not significantly enriched for candidate risk genes. We identify and provide biologic context for 20 genes associated with fibrotic disease of the proximal airway and form the foundation for future detailed genetic study. N/A Laryngoscope, 133:3049-3056, 2023.

Abstract 5633: Analysis of the immune microenvironment and tumor-infiltrating immune cells across different solid tumors by combined spatial transcriptomics and proteomics

Abstract With the advent of immunotherapies such as immune checkpoint inhibitors and CAR T cells, the interest in the tumor microenvironment and tumor-infiltrating lymphocytes (TILs) cells has increased in recent years as these play a critical role in predicting response to therapy and clinical outcomes. We have reported on the identification of potential targets for CAR T cell therapies by analyzing a multitude of tumor samples with hundreds of antibodies by flow cytometry and a new spatial proteomics platform, the MACSima Imaging Platform (Schäfer et al. Nat. Commun., 2021; Kinkhabwala et.al. Sci. Rep., 2022). Here we report on the analysis of tumor microenvironment and tumor infiltrating immune cells using a novel combined spatial transcriptomics and proteomics approach. For protein expression analysis we generated a panel of 60 fluorochrome conjugated antibodies (REAscreen Immuno-oncology, human, FFPE, version 01) selected to identify immune cells, cancer associated fibroblasts, matrix, blood vessels, lymphatics and malignant epithelial cell populations. RNA analysis was based on a novel in situ hybridization and amplification method followed by a cyclic spatial decoding of transcripts (RNAsky). To standardize and further ease the process of protein and RNA detection we generated the antigen and RNA detection probes in a ready-to-use format, i.e., dried and sealed in 96 well plates ready to be inserted into the MACSima. FFPE specimens of different tumor entities reviewed by a pathologist were first hybridized to probes, which were amplified, and spatially decoded by fluorochrome conjugated oligonucleotides. Subsequently the same specimen was exposed to fluorescently labeled antibodies by cycles of antibody reaction, image acquisition and erasure of signal. Finally, specimens were stained with H&E to report on tissue integrity and correlate spatial orientation. The 2D image stacks were analyzed for transcript and antigen quantification and pattern recognition using both, pixel and segmented single-cell data (MACS iQ View Analysis Software). Across the specimens we identified more than 20 cell types including 12 immune cell subsets. The comparison of the tumor microenvironment, tumor-infiltrating immune cells (TILs) and their spatial organization in relation to the tumor cells allowed to identify differences and similarities across the tumor types. In summary we report here on a novel standardized and automated combined spatial RNA and protein expression analysis of the tumor microenvironment and tumor infiltrating immune cells across tumor types. The characterization dataset demonstrates the ability of our platform to perform standardized in-depth phenotyping of sample cohorts. This will enable discovery and further development of predictive and prognostic biomarkers critical to patient stratification for immunotherapy. Citation Format: Julia Femel, Emily Neil, Dongju Park, Fabio El Yassouri, Anijutta Appelshoffer, Erica Lloyd, Michael DiBuono, Henry Sauer, Hanna Lafayette, Hsinyi Smith, Jinling Wang, Dominic Mangiardi, Alex Makrigiorgos, Paurush Praveen, Silvia Rüberg, Werner Müller, Tanya Wantenaar, Robert Pinard, Andreas Bosio. Analysis of the immune microenvironment and tumor-infiltrating immune cells across different solid tumors by combined spatial transcriptomics and proteomics. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5633.

Blocking Abundant RNA Transcripts by High-Affinity Oligonucleotides during Transcriptome Library Preparation

BackgroundRNA sequencing has become the gold standard for transcriptome analysis but has an inherent limitation of challenging quantification of low-abundant transcripts. In contrast to microarray technology, RNA sequencing reads are proportionally divided in function of transcript abundance. Therefore, low-abundant RNAs compete against highly abundant - and sometimes non-informative - RNA species.ResultsWe developed an easy-to-use strategy based on high-affinity RNA-binding oligonucleotides to block reverse transcription and PCR amplification of specific RNA transcripts, thereby substantially reducing their abundance in the final sequencing library. To demonstrate the broad application potential of our method, we applied it to different transcripts and library preparation strategies, including YRNAs in small RNA sequencing of human blood plasma, mitochondrial rRNAs in both 3′ end sequencing and long-read sequencing, and MALAT1 in single-cell 3′ end sequencing. We demonstrate that the blocking strategy is highly efficient, reproducible, specific, and generally results in better transcriptome coverage and complexity.ConclusionOur method does not require modifications of the library preparation procedure apart from simply adding blocking oligonucleotides to the RT reaction and can thus be easily integrated into virtually any RNA sequencing library preparation protocol.

Gene expression of pro-inflammatory (IL-8, IL-18, TNF-α, and IFN-γ) and anti-inflammatory (IL-10) cytokines in the duodenum of broiler chickens exposed to lipopolysaccharides from Escherichia coli and Bacillus subtilis.

Intestinal infections are associated with Gram-negative bacteria like Escherichia coli. When eliminated by treatments during replication, E. coli release lipopolysaccharides (LPS) that can activate the intestinal immune system and increase the expression of cytokines, such as interleukin (IL)-8, IL-18, tumor necrosis factor-alpha (TNF-α), and interferon-gamma (IFN-γ), by the intestinal epithelium under pathological conditions. This study aimed to evaluate the addition of Bacillus subtilis to the duodenal gene expression of pro-inflammatory and anti-inflammatory cytokines in broilers exposed to LPS from E. coli. RNA was extracted using the Zymo Research total RNA commercial kit, according to the manufacturer's specifications, from the intestinal tissue of the duodenum previously resuspended in the lysis buffer of the kit. The expression of the cytokines of interest was measured using the QuantiNova SYBR green real-time polymerase chain reaction kit (Qiagen). Transcript quantification was performed by the ΔΔC(t) method using glyceraldehyde 3-phosphate dehydrogenase as a normalizing constitutive gene. For the measurement of pro-inflammatory (IL-8, IL-18, TNF-α, and IFN-γ) and anti-inflammatory (IL-10) cytokines, there was no statistically significant difference (p > 0.05) between the basal diet and the diet with antibiotic (avilamycin). There was a statistical difference (p < 0.05) between diets with LPS. The diet with B. subtilis presented the lowest expression; the results differed on each sampling day (days 14, 28, and 42). A decrease in the expression of pro-inflammatory cytokines (IL-8, IL-18, TNF-α, and IFN-γ) and an increase in IL-10 (anti-inflammatory) was observed; in this way, a balance of the inflammatory response to bacterial infection is achieved, suggesting that the use of B. subtilis as an additive in a broiler diet has a similar effect to that produced with antibiotic growth promoter.

Benchmark study for evaluating the quality of reference genomes and gene annotations in 114 species.

For reference genomes and gene annotations are key materials that can determine the limits of the molecular biology research of a species; however, systematic research on their quality assessment remains insufficient. We collected reference assemblies, gene annotations, and 3,420 RNA-sequencing (RNA-seq) data from 114 species and selected effective indicators to simultaneously evaluate the reference genome quality of various species, including statistics that can be obtained empirically during the mapping process of short reads. Furthermore, we newly presented and applied transcript diversity and quantification success rates that can relatively evaluate the quality of gene annotations of various species. Finally, we proposed a next-generation sequencing (NGS) applicability index by integrating a total of 10 effective indicators that can evaluate the genome and gene annotation of a specific species. Based on these effective evaluation indicators, we successfully evaluated and demonstrated the relative accessibility of NGS applications in all species, which will directly contribute to determining the technological boundaries in each species. Simultaneously, we expect that it will be a key indicator to examine the direction of future development through relative quality evaluation of genomes and gene annotations in each species, including countless organisms whose genomes and gene annotations will be constructed in the future.

High Expression of CD300A Predicts Poor Survival in Acute Myeloid Leukemia

Introduction: Recent studies have suggested that CD300A was an oncogene in acute myeloid leukemia (AML) development. However, the clinical relevance and biological insight into CD300A expression in AML are still not well understood. The present study aimed to examine the expression characteristics of CD300A in AML and confirmed its clinical significance for AML. Methods: Quantification of the CD300A transcript was performed in 119 AML patients by real-time quantitative PCR in bone marrow blasts. The predictive significance of CD300A expression on the clinical outcomes of AML was assessed using overall survival (OS) and relapse-free survival (RFS). The published Cancer Genome Atlas (TCGA) data were used as an external validation for survival analysis and pathway analyses. Results: In comparison with monocytes from healthy peripheral blood cells, the expression levels of CD300A in AML cells were higher. Patients in the intermediate and adverse risk categories by WHO criteria (2018) had higher CD300A expression levels than those in the favorable risk category (p < 0.001). AML patients with high expression of CD300A had a higher early death rate (p = 0.029), lower complete remission rate (p = 0.042), higher death rate (p < 0.001) and relapse rate (p = 0.002), and shorter OS (p < 0.0001) and RFS (p < 0.0001). Through multivariable analysis, high CD300A expression in AML was also an independent poor prognostic factor. The CAMP and CGMP-PKG signaling pathways may be stimulated by increased CD300A expression levels, which may be important for the development of AML. Conclusions: The expression levels of CD300A were associated with risk stratification and the clinical relevance of AML. High CD300A expression may act as an independent adverse prognostic factor for OS and RFS in AML.

Single-cell RNA-seq analysis reveals dual sensing of HIV-1 in blood Axl+ dendritic cells

Sensing of incoming viruses is a pivotal task of dendritic cells (DCs). Human primary blood DCs encompass various subsets that are diverse in their susceptibility and response to HIV-1. The recent identification of the blood Axl+DC subset, endowed with unique capacities to bind, replicate, and transmit HIV-1 prompted us to evaluate its anti-viral response. We demonstrate that HIV-1 induced two main broad and intense transcriptional programs in different Axl+DCs potentially induced by different sensors; an NF-κB-mediated program that led to DC maturation and efficient CD4+ Tcell activation, and a program mediated by STAT1/2 that activated type I IFN and ISG responses. These responses were absent from cDC2 exposed to HIV-1 except when viral replication was allowed. Finally, Axl+DCs actively replicating HIV-1 identified by quantification of viral transcripts exhibited a mixed NF-κB/ISG innate response. Our results suggest that the route of HIV-1 entry may dictate different innate sensing pathways by DCs.

Haplotype-aware pantranscriptome analyses using spliced pangenome graphs.

Pangenomics is emerging as a powerful computational paradigm in bioinformatics. This field uses population-level genome reference structures, typically consisting of a sequence graph, to mitigate reference bias and facilitate analyses that were challenging with previous reference-based methods. In this work, we extend these methods into transcriptomics to analyze sequencing data using the pantranscriptome: a population-level transcriptomic reference. Our toolchain, which consists of additions to the VG toolkit and a standalone tool, RPVG, can construct spliced pangenome graphs, map RNA sequencing data to these graphs, and perform haplotype-aware expression quantification of transcripts in a pantranscriptome. We show that this workflow improves accuracy over state-of-the-art RNA sequencing mapping methods, and that it can efficiently quantify haplotype-specific transcript expression without needing to characterize the haplotypes of a sample beforehand.

The hitchhikers' guide to RNA sequencing and functional analysis.

DNA and RNA sequencing technologies have revolutionized biology and biomedical sciences, sequencing full genomes and transcriptomes at very high speeds and reasonably low costs. RNA sequencing (RNA-Seq) enables transcript identification and quantification, but once sequencing has concluded researchers can be easily overwhelmed with questions such as how to go from raw data to differential expression (DE), pathway analysis and interpretation. Several pipelines and procedures have been developed to this effect. Even though there is no unique way to perform RNA-Seq analysis, it usually follows these steps: 1) raw reads quality check, 2) alignment of reads to a reference genome, 3) aligned reads' summarization according to an annotation file, 4) DE analysis and 5) gene set analysis and/or functional enrichment analysis. Each step requires researchers to make decisions, and the wide variety of options and resulting large volumes of data often lead to interpretation challenges. There also seems to be insufficient guidance on how best to obtain relevant information and derive actionable knowledge from transcription experiments. In this paper, we explain RNA-Seq steps in detail and outline differences and similarities of different popular options, as well as advantages and disadvantages. We also discuss non-coding RNA analysis, multi-omics, meta-transcriptomics and the use of artificial intelligence methods complementing the arsenal of tools available to researchers. Lastly, we perform a complete analysis from raw reads to DE and functional enrichment analysis, visually illustrating how results are not absolute truths and how algorithmic decisions can greatly impact results and interpretation.

HC-UAP: Outliers detection method based-on hierarchical clustering for universally aligned time-series RNA-Seq profiles

Tracking abundant gene transcripts quantification over continuous cancer progression stages may reveal the mechanism of disease advancement. In this work, we profile the transcript quantification over the stages using a time-series approach, in which the stages/sub-stages of the disease are the time points, and the quantification measurements are the values. The values over time points are used to interpolate the growth of the progression using the cubic spline function. Then, the transcripts profiles are universally aligned and clustered using the time-series profile hierarchical clustering method based on the area between each pair of the aligned profiles; the method is named (HC-UAP). We compare the proposed method with a hierarchical clustering method based on Euclidean distance (HC-ED). Both methods were applied on two next-generation sequencing (NGS) prostate cancer datasets, the first from the Chinese and the second from the North American population. HC-ED clusters the dataset to find patterns while HC-UAP was able to single out outliers that trend differently in both datasets. While finding patterns in gene expression that trend over stages is the standard approach for analyzing time-series models, identifying outlier transcripts that grow differently than other transcripts can provide more details about the contribution of the mRNA transcriptional activity to the disease. They also can be a potential biomarker for the disease progression.

Quantitative Measurements of Biochemical and Molecular Markers of Oxidative Stress Signaling and Responses.

Increases in cellular oxidation are a part of most plant responses to challenging conditions and are commonly described as oxidative stress. While this phenomenon is closely related to the accumulation of reactive oxygen species, these latter compounds can be difficult to measure. Complementary measurements to assess cellular redox state are, therefore, very useful in studies of plant responses to stress. Here, we detail protocols for three complementary approaches that can be used to assess the intensity of oxidative stress. These involve quantification of marker transcripts, assays of the extractable activities of major antioxidative enzymes, and measurement of antioxidant buffers. We confirm experimentally that the data obtained by such approaches can provide reliable information on the intensity of oxidative stress.

Quantitative Analysis of Gene Expression in RNAscope-processed Brain Tissue.

Molecular characterization of different cell types in rodent brains is a widely used and important approach in neuroscience. Fluorescent detection of transcripts using RNAscope (ACDBio) has quickly became a standard in situ hybridization (ISH) approach. Its sensitivity and specificity allow for the simultaneous detection of between three and forty-eight low abundance mRNAs in single cells (i.e., multiplexing or hiplexing), and, in contrast to other ISH techniques, it is performed in a shorter amount of time. Manual quantification of transcripts is a laborious and time-consuming task even for small portions of a larger tissue section. Herein, we present a protocol for creating high-quality images for quantification of RNAscope-labeled neurons in the rat brain. This protocol uses custom-made scripts within the open-source software QuPath to create an automated workflow for the careful optimization and validation of cell detection parameters. Moreover, we describe a method to derive mRNA signal thresholds using negative controls. This protocol and automated workflow may help scientists to reliably and reproducibly prepare and analyze rodent brain tissue for cell type characterization using RNAscope. Graphical abstract.

Susceptibilities of CNS Cells towards Rabies Virus Infection Is Linked to Cellular Innate Immune Responses.

Rabies is caused by neurotropic rabies virus (RABV), contributing to 60,000 human deaths annually. Even though rabies leads to major public health concerns worldwide, we still do not fully understand factors determining RABV tropism and why glial cells are unable to clear RABV from the infected brain. Here, we compare susceptibilities and immune responses of CNS cell types to infection with two RABV strains, Tha and its attenuated variant Th2P-4M, mutated on phospho- (P-protein) and matrix protein (M-protein). We demonstrate that RABV replicates in human stem cell-derived neurons and astrocytes but fails to infect human iPSC-derived microglia. Additionally, we observed major differences in transcription profiles and quantification of intracellular protein levels between antiviral immune responses mediated by neurons, astrocytes (IFNB1, CCL5, CXCL10, IL1B, IL6, and LIF), and microglia (CCL5, CXCL10, ISG15, MX1, and IL6) upon Tha infection. We also show that P- and M-proteins of Tha mediate evasion of NF-κB- and JAK-STAT-controlled antiviral host responses in neuronal cell types in contrast to glial cells, potentially explaining the strong neuron-specific tropism of RABV. Further, Tha-infected astrocytes and microglia protect neurons from Tha infection via a filtrable and transferable agent. Overall, our study provides novel insights into RABV tropism, showing the interest in studying the interplay of CNS cell types during RABV infection.

Spinosad‐associated modulation of select cytochrome P450s and glutathione S‐transferases in the Colorado potato beetle, Leptinotarsa decemlineata

The Colorado potato beetle (Leptinotarsa decemlineata (Say)) is an insect pest that threatens potato crops. Multiple options exist to limit the impact of this pest even though insecticides remain a primary option for its control. Insecticide resistance has been reported in Colorado potato beetles and a better understanding of the molecular players underlying such process is of utmost importance to optimize the tools used to mitigate the impact of this insect. Resistance against the insecticide spinosad has been reported in this insect and this work thus aims at exploring the expression of targets previously associated with insecticide response in Colorado potato beetles exposed to this compound. Amplification and quantification of transcripts coding for cytochrome P450s and glutathione S-transferases were conducted via qRT-PCR in insects treated with varying doses of spinosad and for different time duration. This approach notably revealed differential expression of CYP6a23 and CYP12a5 in insects exposed to low doses of spinosad for 4 has well as modulation of CYP6a13, CYP6d4, GST, GST1, and GST1-Like in insects treated with high doses of spinosad for the same duration. RNAi-based targeting of CYP4g15 and CYP6a23 was associated with marked reduction of transcript expression 7days following dsRNA injection and reduction of the former had a marked impact on insect viability. In general, results presented here provide novel information regarding the expression of transcripts relevant to spinosad response in Colorado potato beetles and reveal a novel target to consider in the development of RNAi-based strategies aimed at this potato pest.