A protocol to evaluate RNA sequencing normalization methods

Dynamic changes in mRNA nucleocytoplasmic localization in the nitrate response of Arabidopsis roots

Nitrate is a nutrient and signal that regulates gene expression. The nitrate response has been extensively characterized at the organism, organ, and cell-type-specific levels, but intracellular mRNA dynamics remain unexplored. To characterize nuclear and cytoplasmic transcriptome dynamics in response to nitrate, we performed a time-course expression analysis after nitrate treatment in isolated nuclei, cytoplasm, and whole roots. We identified 402 differentially localized transcripts (DLTs) in response to nitrate treatment. Induced DLT genes showed rapid and transient recruitment of the RNA polymerase II, together with an increase in the mRNA turnover rates. DLTs code for genes involved in metabolic processes, localization, and response to stimulus indicating DLTs include genes with relevant functions for the nitrate response that have not been previously identified. Using single-molecule RNA FISH, we observed early nuclear accumulation of the NITRATE REDUCTASE 1 (NIA1) transcripts in their transcription sites. We found that transcription of NIA1, a gene showing delayed cytoplasmic accumulation, is rapidly and transiently activated; however, its transcripts become unstable when they reach the cytoplasm. Our study reveals the dynamic localization of mRNAs between the nucleus and cytoplasm as an emerging feature in the temporal control of gene expression in response to nitrate treatment in Arabidopsis roots.

De novo assembly of transcriptomes and differential gene expression analysis using short-read data from emerging model organisms - a brief guide

Many questions in biology benefit greatly from the use of a variety of model systems. High-throughput sequencing methods have been a triumph in the democratization of diverse model systems. They allow for the economical sequencing of an entire genome or transcriptome of interest, and with technical variations can even provide insight into genome organization and the expression and regulation of genes. The analysis and biological interpretation of such large datasets can present significant challenges that depend on the 'scientific status' of the model system. While high-quality genome and transcriptome references are readily available for well-established model systems, the establishment of such references for an emerging model system often requires extensive resources such as finances, expertise and computation capabilities. The de novo assembly of a transcriptome represents an excellent entry point for genetic and molecular studies in emerging model systems as it can efficiently assess gene content while also serving as a reference for differential gene expression studies. However, the process of de novo transcriptome assembly is non-trivial, and as a rule must be empirically optimized for every dataset. For the researcher working with an emerging model system, and with little to no experience with assembling and quantifying short-read data from the Illumina platform, these processes can be daunting. In this guide we outline the major challenges faced when establishing a reference transcriptome de novo and we provide advice on how to approach such an endeavor. We describe the major experimental and bioinformatic steps, provide some broad recommendations and cautions for the newcomer to de novo transcriptome assembly and differential gene expression analyses. Moreover, we provide an initial selection of tools that can assist in the journey from raw short-read data to assembled transcriptome and lists of differentially expressed genes.

NTpred: a robust and precise machine learning framework for in silico identification of Tyrosine nitration sites in protein sequences

Post-translational modifications (PTMs) either enhance a protein's activity in various sub-cellular processes, or degrade their activity which leads toward failure of intracellular processes. Tyrosine nitration (NT) modification degrades protein's activity that initiates and propagates various diseases including neurodegenerative, cardiovascular, autoimmune diseases and carcinogenesis. Identification of NT modification supports development of novel therapies and drug discoveries for associated diseases. Identification of NT modification in biochemical labs is expensive, time consuming and error-prone. To supplement this process, several computational approaches have been proposed. However these approaches fail to precisely identify NT modification, due to the extraction of irrelevant, redundant and less discriminative features from protein sequences. This paper presents the NTpred framework that is competent in extracting comprehensive features from raw protein sequences using four different sequence encoders. To reap the benefits of different encoders, it generates four additional feature spaces by fusing different combinations of individual encodings. Furthermore, it eradicates irrelevant and redundant features from eight different feature spaces through a Recursive Feature Elimination process. Selected features of four individual encodings and four feature fusion vectors are used to train eight different Gradient Boosted Tree classifiers. The probability scores from the trained classifiers are utilized to generate a new probabilistic feature space, which is used to train a Logistic Regression classifier. On the BD1 benchmark dataset, the proposed framework outperforms the existing best-performing predictor in 5-fold cross validation and independent test evaluation with combined improvement of 13.7% in MCC and 20.1% in AUC. Similarly, on the BD2 benchmark dataset, the proposed framework outperforms the existing best-performing predictor with combined improvement of 5.3% in MCC and 1.0% in AUC. NTpred is publicly available for further experimentation and predictive use at: https://sds_genetic_analysis.opendfki.de/PredNTS/.

Tissue-specific RNA methylation prediction from gene expression data using sparse regression models

N6-methyladenosine (m6A) is a highly prevalent and conserved post-transcriptional modification observed in mRNA and long non-coding RNA (lncRNA). Identifying potential m6A sites within RNA sequences is crucial for unraveling the potential influence of the epitranscriptome on biological processes. In this study, we introduce Exp2RM, a novel approach that formulates single-site-based tissue-specific elastic net models for predicting tissue-specific methylation levels utilizing gene expression data. The resulting ensemble model demonstrates robust predictive performance for tissue-specific methylation levels, with an average R-squared value of 0.496 and a median R-squared value of 0.482 across all 22 human tissues. Since methylation distribution varies among tissues, we trained the model to incorporate similar patterns, significantly improves accuracy with the median R-squared value increasing to 0.728. Additonally, functional analysis reveals Exp2RM's ability to capture coefficient genes in relevant biological processes. This study emphasizes the importance of tissue-specific methylation distribution in enhancing prediction accuracy and provides insights into the functional implications of methylation sites.

Zero is not absence: censoring-based differential abundance analysis for microbiome data

MOTIVATION

Microbiome data analysis faces the challenge of sparsity, with many entries recorded as zeros. In differential abundance analysis, the presence of excessive zeros in data violates distributional assumptions and creates ties, leading to an increased risk of type I errors and reduced statistical power.

RESULTS

We developed a novel normalization method, called censoring-based analysis of microbiome proportions (CAMP), for microbiome data by treating zeros as censored observations, transforming raw read counts into tie-free time-to-event-like data. This enables the use of survival analysis techniques, like the Cox proportional hazards model, for differential abundance analysis. Extensive simulations demonstrate that CAMP achieves proper type I error control and high power. Applying CAMP to a human gut microbiome dataset, we identify 60 new differentially abundant taxa across geographic locations, showcasing its usefulness. CAMP overcomes sparsity challenges, enabling improved statistical analysis and providing valuable insights into microbiome data in various contexts.

AVAILABILITY AND IMPLEMENTATION

The R package is available at https://github.com/lapsumchan/CAMP.

Microbial dynamics in soils of the Damma glacier forefield show succession in the functional genetic potential

Glacier retreat is a visible consequence of climate change worldwide. Although taxonomic change of the soil microbiomes in glacier forefields have been widely documented, how microbial genetic potential changes along succession is little known. Here, we used shotgun metagenomics to analyse whether the soil microbial genetic potential differed between four stages of soil development (SSD) sampled along three transects in the Damma glacier forefield (Switzerland). The SSDs were characterized by an increasing vegetation cover, from barren soil, to biological soil crust, to sparsely vegetated soil and finally to vegetated soil. Results suggested that SSD significantly influenced microbial genetic potential, with the lowest functional diversity surprisingly occurring in the vegetated soils. Overall, carbohydrate metabolism and secondary metabolite biosynthesis genes overrepresented in vegetated soils, which could be partly attributed to plant-soil feedbacks. For C degradation, glycoside hydrolase genes enriched in vegetated soils, while auxiliary activity and carbohydrate esterases genes overrepresented in barren soils, suggested high labile C degradation potential in vegetated, and high recalcitrant C degradation potential in barren soils. For N-cycling, organic N degradation and synthesis genes dominated along succession, and gene families involved in nitrification were overrepresented in barren soils. Our study provides new insights into how the microbial genetic potential changes during soil formation along the Damma glacier forefield.

Statistical normalization methods in microbiome data with application to microbiome cancer research

Mounting evidence has shown that gut microbiome is associated with various cancers, including gastrointestinal (GI) tract and non-GI tract cancers. But microbiome data have unique characteristics and pose major challenges when using standard statistical methods causing results to be invalid or misleading. Thus, to analyze microbiome data, it not only needs appropriate statistical methods, but also requires microbiome data to be normalized prior to statistical analysis. Here, we first describe the unique characteristics of microbiome data and the challenges in analyzing them (Section 2). Then, we provide an overall review on the available normalization methods of 16S rRNA and shotgun metagenomic data along with examples of their applications in microbiome cancer research (Section 3). In Section 4, we comprehensively investigate how the normalization methods of 16S rRNA and shotgun metagenomic data are evaluated. Finally, we summarize and conclude with remarks on statistical normalization methods (Section 5). Altogether, this review aims to provide a broad and comprehensive view and remarks on the promises and challenges of the statistical normalization methods in microbiome data with microbiome cancer research examples.

Transcriptomic investigation of the molecular mechanisms underlying resistance to the neonicotinoid thiamethoxam and the pyrethroid lambda-cyhalothrin in Euschistus heros (Hemiptera: Pentatomidae)

BACKGROUND

Laboratory-selected resistant strains of Euschistus heros to thiamethoxam (NEO) and lambda-cyhalothrin (PYR) were recently reported in Brazil. However, the mechanisms conferring resistance to these insecticides in E. heros remain unresolved. We utilized comparative transcriptome profiling and single nucleotide polymorphism (SNP) calling of susceptible and resistant strains of E. heros to investigate the molecular mechanism(s) underlying resistance.

RESULTS

The E. heros transcriptome was assembled, generating 91 673 transcripts with a mean length of 720 bp and N50 of 1795 bp. Comparative gene expression analysis between the susceptible (SUS) and NEO strains identified 215 significantly differentially expressed (DE) transcripts. DE transcripts associated with the xenobiotic metabolism were all up-regulated in the NEO strain. The comparative analysis of the SUS and PYR strains identified 204 DE transcripts, including an esterase (esterase FE4), a glutathione-S-transferase, an ABC transporter (ABCC1) and aquaporins that were up-regulated in the PYR strain. We identified 9588 and 15 043 nonsynonymous SNPs in the PYR and NEO strains. One of the SNPs (D70N) detected in the NEO strain occurs in a subunit (α5) of the nAChRs, the target site of neonicotinoid insecticides. Nevertheless, this residue position in α5 is not conserved among insects.

CONCLUSIONS

Neonicotinoid and pyrethroid resistance in laboratory-selected E. heros is associated with a potential metabolic resistance mechanism by the overexpression of proteins commonly involved in the three phases of xenobiotic metabolism. Together these findings provide insight into the potential basis of resistance in E. heros and will inform the development and implementation of resistance management strategies against this important pest. © 2023 Society of Chemical Industry.

Integrative bioinformatics analysis of WDHD1: a potential biomarker for pan-cancer prognosis, diagnosis, and immunotherapy

BACKGROUND

Although WD repeat and high-mobility group box DNA binding protein 1 (WDHD1) played an essential role in DNA replication, chromosome stability, and DNA damage repair, the panoramic picture of WDHD1 in human tumors remains unclear. Hence, this study aims to comprehensively characterize WDHD1 across 33 human cancers.

METHODS

Based on publicly available databases such as TCGA, GTEx, and HPA, we used a bioinformatics approach to systematically explore the genomic features and biological functions of WDHD1 in pan-cancer.

RESULTS

WDHD1 mRNA levels were significantly increased in more than 20 types of tumor tissues. Elevated WDHD1 expression was associated with significantly shorter overall survival (OS) in 10 tumors. Furthermore, in uterine corpus endometrial carcinoma (UCEC) and liver hepatocellular carcinoma (LIHC), WDHD1 expression was significantly associated with higher histological grades and pathological stages. In addition, WDHD1 had a high diagnostic value among 16 tumors (area under the ROC curve [AUC] > 0.9). Functional enrichment analyses suggested that WDHD1 probably participated in many oncogenic pathways such as E2F and MYC targets (false discovery rate [FDR] < 0.05), and it was involved in the processes of DNA replication and DNA damage repair (p.adjust < 0.05). WDHD1 expression also correlated with the half-maximal inhibitory concentrations (IC50) of rapamycin (4 out of 10 cancers) and paclitaxel (10 out of 10 cancers). Overall, WDHD1 was negatively associated with immune cell infiltration and might promote tumor immune escape. Our analysis of genomic alterations suggested that WDHD1 was altered in 1.5% of pan-cancer cohorts and the "mutation" was the predominant type of alteration. Finally, through correlation analysis, we found that WDHD1 might be closely associated with tumor heterogeneity, tumor stemness, mismatch repair (MMR), and RNA methylation modification, which were all processes associated with the tumor progression.

CONCLUSIONS

Our pan-cancer analysis of WDHD1 provides valuable insights into the genomic characterization and biological functions of WDHD1 in human cancers and offers some theoretical support for the future use of WDHD1-targeted therapies, immunotherapies, and chemotherapeutic combinations for the management of tumors.

Variability in donor leukocyte counts confound the use of common RNA sequencing data normalization strategies in transcriptomic biomarker studies performed with whole blood

Gene expression data generated from whole blood via next generation sequencing is frequently used in studies aimed at identifying mRNA-based biomarker panels with utility for diagnosis or monitoring of human disease. These investigations often employ data normalization techniques more typically used for analysis of data originating from solid tissues, which largely operate under the general assumption that specimens have similar transcriptome composition. However, this assumption may be violated when working with data generated from whole blood, which is more cellularly dynamic, leading to potential confounds. In this study, we used next generation sequencing in combination with flow cytometry to assess the influence of donor leukocyte counts on the transcriptional composition of whole blood specimens sampled from a cohort of 138 human subjects, and then subsequently examined the effect of four frequently used data normalization approaches on our ability to detect inter-specimen biological variance, using the flow cytometry data to benchmark each specimens true cellular and molecular identity. Whole blood samples originating from donors with differing leukocyte counts exhibited dramatic differences in both genome-wide distributions of transcript abundance and gene-level expression patterns. Consequently, three of the normalization strategies we tested, including median ratio (MRN), trimmed mean of m-values (TMM), and quantile normalization, noticeably masked the true biological structure of the data and impaired our ability to detect true interspecimen differences in mRNA levels. The only strategy that improved our ability to detect true biological variance was simple scaling of read counts by sequencing depth, which unlike the aforementioned approaches, makes no assumptions regarding transcriptome composition.

Day-night fluctuations in choroid plexus transcriptomics and cerebrospinal fluid metabolomics

The cerebrospinal fluid (CSF) provides mechanical protection for the brain and serves as a brain dispersion route for nutrients, hormones, and metabolic waste. The CSF secretion rate is elevated in the dark phase in both humans and rats, which could support the CSF flow along the paravascular spaces that may be implicated in waste clearance. The similar diurnal CSF dynamics pattern observed in the day-active human and the nocturnal rat suggests a circadian regulation of this physiological variable, rather than sleep itself. To obtain a catalog of potential molecular drivers that could provide the day-night-associated modulation of the CSF secretion rate, we determined the diurnal fluctuation in the rat choroid plexus transcriptomic profile with RNA-seq and in the CSF metabolomics with ultraperformance liquid chromatography combined with mass spectrometry. We detected significant fluctuation of 19 CSF metabolites and differential expression of 2,778 choroid plexus genes between the light and the dark phase, the latter of which encompassed circadian rhythm-related genes and several choroid plexus transport mechanisms. The fluctuating components were organized with joint pathway analysis, of which several pathways demonstrated diurnal regulation. Our results illustrate substantial transcriptional and metabolic light-dark phase-mediated changes taking place in the rat choroid plexus and its encircling CSF. The combined data provide directions toward future identification of the molecular pathways governing the fluctuation of this physiological process and could potentially be harnessed to modulate the CSF dynamics in pathology.

Nocturnal increase in cerebrospinal fluid secretion as a circadian regulator of intracranial pressure

BACKGROUND

It is crucial to maintain the intracranial pressure (ICP) within the physiological range to ensure proper brain function. The ICP may fluctuate during the light-dark phase cycle, complicating diagnosis and treatment choice in patients with pressure-related disorders. Such ICP fluctuations may originate in circadian or sleep-wake cycle-mediated modulation of cerebrospinal fluid (CSF) flow dynamics, which in addition could support diurnal regulation of brain waste clearance.

METHODS

ICP was monitored continuously in patients who underwent placement of an external ventricular drain (EVD) and by telemetric monitoring in experimental rats. CSF was collected via the EVD in patients and the rodent CSF secretion rate determined by in vivo experimentation. Rodent choroid plexus transporter transcripts were quantified with RNAseq and transport activity with ex vivo isotope transport assays.

RESULTS

We demonstrated that ICP increases by 30% in the dark phase in both species, independently of vascular parameters. This increase aligns with elevated CSF collection in patients (12%) and CSF production rate in rats (20%), the latter obtained with the ventriculo-cisternal perfusion assay. The dark-phase increase in CSF secretion in rats was, in part, assigned to increased transport activity of the choroid plexus Na⁺,K⁺,2Cl^- cotransporter (NKCC1), which is implicated in CSF secretion by this tissue.

CONCLUSION

CSF secretion, and thus ICP, increases in the dark phase in humans and rats, irrespective of their diurnal/nocturnal activity preference, in part due to altered choroid plexus transport activity in the rat. Our findings suggest that CSF dynamics are modulated by the circadian rhythm, rather than merely sleep itself.

NORMSEQ: a tool for evaluation, selection and visualization of RNA-Seq normalization methods

RNA-sequencing has become one of the most used high-throughput approaches to gain knowledge about the expression of all different RNA subpopulations. However, technical artifacts, either introduced during library preparation and/or data analysis, can influence the detected RNA expression levels. A critical step, especially in large and low input datasets or studies, is data normalization, which aims at eliminating the variability in data that is not related to biology. Many normalization methods have been developed, each of them relying on different assumptions, making the selection of the appropriate normalization strategy key to preserve biological information. To address this, we developed NormSeq, a free web-server tool to systematically assess the performance of normalization methods in a given dataset. A key feature of NormSeq is the implementation of information gain to guide the selection of the best normalization method, which is crucial to eliminate or at least reduce non-biological variability. Altogether, NormSeq provides an easy-to-use platform to explore different aspects of gene expression data with a special focus on data normalization to help researchers, even without bioinformatics expertise, to obtain reliable biological inference from their data. NormSeq is freely available at: https://arn.ugr.es/normSeq.

Clinically important alterations in pharmacogene expression in histologically severe nonalcoholic fatty liver disease

Polypharmacy is common in patients with nonalcoholic fatty liver disease (NAFLD) and previous reports suggest that NAFLD is associated with altered drug disposition. This study aims to determine if patients with NAFLD are at risk for altered drug response by characterizing changes in hepatic mRNA expression of genes mediating drug disposition (pharmacogenes) across the histological NAFLD severity spectrum. We utilize RNA-seq for 93 liver biopsies with histologically staged NAFLD Activity Score (NAS), fibrosis stage, and steatohepatitis (NASH). We identify 37 significant pharmacogene-NAFLD severity associations including CYP2C19 downregulation. We chose to validate CYP2C19 due to its actionability in drug prescribing. Meta-analysis of 16 independent studies demonstrate that CYP2C19 is significantly downregulated to 46% in NASH, to 58% in high NAS, and to 43% in severe fibrosis. Our data demonstrate the downregulation of CYP2C19 in NAFLD which supports developing personalized medicine approaches for drugs sensitive to metabolism by the CYP2C19 enzyme.

Bacterial aerobic methane cycling by the marine sponge-associated microbiome

BACKGROUND

Methanotrophy by the sponge-hosted microbiome has been mainly reported in the ecological context of deep-sea hydrocarbon seep niches where methane is either produced geothermically or via anaerobic methanogenic archaea inhabiting the sulfate-depleted sediments. However, methane-oxidizing bacteria from the candidate phylum Binatota have recently been described and shown to be present in oxic shallow-water marine sponges, where sources of methane remain undescribed.

RESULTS

Here, using an integrative -omics approach, we provide evidence for sponge-hosted bacterial methane synthesis occurring in fully oxygenated shallow-water habitats. Specifically, we suggest methane generation occurs via at least two independent pathways involving methylamine and methylphosphonate transformations that, concomitantly to aerobic methane production, generate bioavailable nitrogen and phosphate, respectively. Methylphosphonate may be sourced from seawater continuously filtered by the sponge host. Methylamines may also be externally sourced or, alternatively, generated by a multi-step metabolic process where carnitine, derived from sponge cell debris, is transformed to methylamine by different sponge-hosted microbial lineages. Finally, methanotrophs specialized in pigment production, affiliated to the phylum Binatota, may provide a photoprotective function, closing a previously undescribed C₁-metabolic loop that involves both the sponge host and specific members of the associated microbial community.

CONCLUSION

Given the global distribution of this ancient animal lineage and their remarkable water filtration activity, sponge-hosted methane cycling may affect methane supersaturation in oxic coastal environments. Depending on the net balance between methane production and consumption, sponges may serve as marine sources or sinks of this potent greenhouse gas. Video Abstract.

Yersiniomics, a Multi-Omics Interactive Database for Yersinia Species

The genus Yersinia includes a large variety of nonpathogenic and life-threatening pathogenic bacteria, which cause a broad spectrum of diseases in humans and animals, such as plague, enteritis, Far East scarlet-like fever (FESLF), and enteric redmouth disease. Like most clinically relevant microorganisms, Yersinia spp. are currently subjected to intense multi-omics investigations whose numbers have increased extensively in recent years, generating massive amounts of data useful for diagnostic and therapeutic developments. The lack of a simple and centralized way to exploit these data led us to design Yersiniomics, a web-based platform allowing straightforward analysis of Yersinia omics data. Yersiniomics contains a curated multi-omics database at its core, gathering 200 genomic, 317 transcriptomic, and 62 proteomic data sets for Yersinia species. It integrates genomic, transcriptomic, and proteomic browsers, a genome viewer, and a heatmap viewer to navigate within genomes and experimental conditions. For streamlined access to structural and functional properties, it directly links each gene to GenBank, the Kyoto Encyclopedia of Genes and Genomes (KEGG), UniProt, InterPro, IntAct, and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and each experiment to Gene Expression Omnibus (GEO), the European Nucleotide Archive (ENA), or the Proteomics Identifications Database (PRIDE). Yersiniomics provides a powerful tool for microbiologists to assist with investigations ranging from specific gene studies to systems biology studies. IMPORTANCE The expanding genus Yersinia is composed of multiple nonpathogenic species and a few pathogenic species, including the deadly etiologic agent of plague, Yersinia pestis. In 2 decades, the number of genomic, transcriptomic, and proteomic studies on Yersinia grew massively, delivering a wealth of data. We developed Yersiniomics, an interactive web-based platform, to centralize and analyze omics data sets on Yersinia species. The platform allows user-friendly navigation between genomic data, expression data, and experimental conditions. Yersiniomics will be a valuable tool to microbiologists.

Comparative phylogenomic and structural analysis of canonical secretory PLA2 and novel PLA2-like family in plants

Plant secretory phospholipase A₂ (sPLA₂) is a family of lipolytic enzymes involved in the sn-2 hydrolysis of phospholipid carboxyester bonds, characterized by the presence of a conserved PA2c domain. PLA₂ produces free fatty acids and lysophospholipids, which regulate several physiological functions, including lipid metabolism, plant growth and development, signal transduction, and response to various environmental stresses. In the present work, we have performed a comparative analysis of PA2c domain-containing genes across plants, focusing on gene distribution, phylogenetic analysis, tissue-specific expression, and homology modeling. Our data revealed the widespread occurrence of multiple sPLA₂ in most land plants and documented single sPLA₂ in multiple algal groups, indicating an ancestral origin of sPLA₂. We described a novel PA2c-containing gene family present in all plant lineages and lacking secretory peptide, which we termed PLA₂-like. Phylogenetic analysis revealed two independent clades in canonical sPLA₂ genes referred to as α and β clades, whereas PLA₂-like genes clustered independently as a third clade. Further, we have explored clade-specific gene expressions showing that while all three clades were expressed in vegetative and reproductive tissues, only sPLA₂-β and PLA₂-like members were expressed in the pollen and pollen tube. To get insight into the conservation of the gene regulatory network of sPLA₂ and PLA₂-like genes, we have analyzed the occurrence of various cis-acting promoter elements across the plant kingdom. The comparative 3D structure analysis revealed conserved and unique features within the PA2c domain for the three clades. Overall, this study will help to understand the evolutionary significance of the PA2c family and lay the foundation for future sPLA₂ and PLA₂-like characterization in plants.

Data-Driven Identification of Targets for Fluorescence-Guided Surgery in Non-Small Cell Lung Cancer

PURPOSE

Intraoperative identification of lung tumors can be challenging. Tumor-targeted fluorescence-guided surgery can provide surgeons with a tool for real-time intraoperative tumor detection. This study evaluated cell surface biomarkers, partially selected via data-driven selection software, as potential targets for fluorescence-guided surgery in non-small cell lung cancers: adenocarcinomas (ADC), adenocarcinomas in situ (AIS), and squamous cell carcinomas (SCC).

PROCEDURES

Formalin-fixed paraffin-embedded tissue slides of resection specimens from 15 patients with ADC and 15 patients with SCC were used and compared to healthy tissue. Molecular targets were selected based on two strategies: (1) a data-driven selection using > 275 multi-omics databases, literature, and experimental evidence; and (2) the availability of a fluorescent targeting ligand in advanced stages of clinical development. The selected targets were carbonic anhydrase 9 (CAIX), collagen type XVII alpha 1 chain (collagen XVII), glucose transporter 1 (GLUT1), G protein-coupled receptor 87 (GPR87), transmembrane protease serine 4 (TMPRSS4), carcinoembryonic antigen (CEA), epithelial cell adhesion molecule (EpCAM), folate receptor alpha (FRα), integrin αvβ6 (αvβ6), and urokinase-type plasminogen activator receptor (uPAR). Tumor expression of these targets was assessed by immunohistochemical staining. A total immunostaining score (TIS, range 0-12), combining the percentage and intensity of stained cells, was calculated. The most promising targets in ADC were explored in six AIS tissue slides to explore its potential in non-palpable lesions.

RESULTS

Statistically significant differences in TIS between healthy lung and tumor tissue for ADC samples were found for CEA, EpCAM, FRα, αvβ6, CAIX, collagen XVII, GLUT-1, and TMPRSS4, and of these, CEA, CAIX, and collagen XVII were also found in AIS. For SCC, EpCAM, uPAR, CAIX, collagen XVII, and GLUT-1 were found to be overexpressed.

CONCLUSIONS

EpCAM, CAIX, and Collagen XVII were identified using concomitant use of data-driven selection software and clinical evidence as promising targets for intraoperative fluorescence imaging for both major subtypes of non-small cell lung carcinomas.

Transformer fault diagnosis research based on LIF technology and IAO optimization of LightGBM

Transformer fault diagnosis is a necessary operation to ensure the stable operation of a power system. In view of the problems of the low diagnostic rate and long time needed in traditional methods, such as the dissolved gas in oil method, a laser-induced fluorescence (LIF) spectral technology is proposed in this paper, which incorporated an improved aquila optimizer (IAO) and light gradient boosting machine (LightGBM), to predict the types of transformer faults. The original AO was improved using the Nelder Mead (NM) simple search method and opposition-based learning (OBL) mechanism, which could improve the parameter optimization ability of the model. Normal oil, thermal fault oil, local moisture oil, and electrical fault oil were selected as experimental samples. First, the spectral images of the four oil samples were obtained by LIF technology, and the fluorescence spectral curves obtained were preprocessed by multivariate scattering correction (MSC) and normalization (normalize), while kernel-based principle component analysis (KPCA) was used for dimensional reduction. The dimensionality-reduced data were then imported into the LightGBM model for training, and the IAO algorithm was used to optimize the parameters of the LightGBM. Finally, the experiment showed that the LIF technology demonstrated good recognition of the fault types for transformer fault diagnosis; the data purity after MSC preprocessing was higher than that of other processing methods; the prediction effect of the LightGBM model was superior to other prediction models; the LightGBM model optimized by IAO had better convergence, parameter optimization ability, and prediction accuracy than the LightGBM model optimized by the original AO and particle swarm optimization (PSO). Among the models, the MSC-IAO-LightGBM model had the best effect on fault prediction, with the mean square error (MSE) reaching 9.0643 × 10-7, mean absolute error (MAE) reaching 8.7439 × 10-4, and goodness of fit (R2) approaching 1. It can be implemented as a new diagnostic method in transformer fault detection, which is of great significance to ensure the stable and safe operation of power systems.

Quantification of spatial pharmacogene expression heterogeneity in breast tumors

BACKGROUND

Chemotherapeutic drug concentrations vary across different regions of tumors and this is thought to be involved in development of chemotherapy resistance. Insufficient drug delivery to some regions of the tumor may be due to spatial differences in expression of genes involved in the disposition, transport, and detoxification of drugs (pharmacogenes). Therefore, in this study, we analyzed the spatial expression of 286 pharmacogenes in six breast cancer tissues using the recently developed Visium spatial transcriptomics platform to (1) determine if these pharmacogenes are expressed heterogeneously across tumor tissue and (2) to determine which pharmacogenes have the most spatial expression heterogeneity.

METHODS AND RESULTS

The spatial transcriptomics technology sequences the transcriptome of 55 um diameter barcoded sections (spots) across a tissue sample. We analyzed spatial gene expression profiles of four biobank-sourced breast tumor samples in addition to two breast tumor sample datasets from 10× Genomics. We define heterogeneity as the interquartile range of read counts. Collectively, we identified 8887 spots in tumor regions, 3814 in stroma, 44 in lymphocytes, and 116 in normal regions based on pathologist annotation of the tissues. We showed statistically significant differences in expression of pharmacogenes in tumor regions compared to surrounding non-tumor regions. We also observed that the most heterogeneously expressed genes within tumor regions were involved in reactive oxygen species (ROS) handling and detoxification mechanisms. GPX4, GSTP1, MGST3, SOD1, CYP4Z1, CYB5R3, GSTK1, and NAT1 showed the most heterogeneous expression within tumor regions.

CONCLUSIONS

The heterogeneous expression of these pharmacogenes may have important implications for cancer therapy due to their ability to impact drug distribution and efficacy throughout the tumor. Our results suggest that chemoresistance caused by expression of GPX4, GSTP1, MGST3, and SOD1 may be intrinsic, not acquired, since the heterogeneity is not specific to chemotherapy-treated samples or cell type. Additionally, we identified candidate chemoresistance pharmacogenes that can be further tested through focused follow-up studies.

Ecoimmunology in the field: Measuring multiple dimensions of immune function with minimally invasive, field-adapted techniques

OBJECTIVE

Immune function is multifaceted and characterizations based on single biomarkers may be uninformative or misleading, particularly when considered across ecological contexts. However, measuring the many facets of immunity in the field can be challenging, since many measures cannot be obtained on-site, necessitating sample preservation and transport. Here we assess state-of-the-art methods for measuring immunity, focusing on measures that require a minimal blood sample obtained from a finger prick, which can be: (1) dried on filter paper, (2) frozen in liquid nitrogen, or (3) stabilized with chemical reagents.

RESULTS

We review immune measures that can be obtained from point-of-care devices or from immunoassays of dried blood spots (DBSs), field methods for flow cytometry, the use of RNA or DNA sequencing and quantification, and the application of immune activation assays under field conditions.

CONCLUSIONS

Stable protein products, such as immunoglobulins and C-reactive protein are reliably measured in DBSs. Because less stable proteins, such as cytokines, may be problematic to measure even in fresh blood, mRNA from stabilized blood may provide a cleaner measure of cytokine and broader immune-related gene expression. Gene methylation assays or mRNA sequencing also allow for the quantification of many other parameters, including the inference of leukocyte subsets, though with less accuracy than with flow cytometry. Combining these techniques provides an improvement over single-marker studies, allowing for a more nuanced understanding of how social and ecological variables are linked to immune measures and disease risk in diverse populations and settings.

Lysophosphatidic acid as a CSF lipid in posthemorrhagic hydrocephalus that drives CSF accumulation via TRPV4-induced hyperactivation of NKCC1

Background

A range of neurological pathologies may lead to secondary hydrocephalus. Treatment has largely been limited to surgical cerebrospinal fluid (CSF) diversion, as specific and efficient pharmacological options are lacking, partly due to the elusive molecular nature of the CSF secretion apparatus and its regulatory properties in physiology and pathophysiology.

Methods

CSF obtained from patients with subarachnoid hemorrhage (SAH) and rats with experimentally inflicted intraventricular hemorrhage (IVH) was analyzed for lysophosphatidic acid (LPA) by alpha-LISA. We employed the in vivo rat model to determine the effect of LPA on ventricular size and brain water content, and to reveal the effect of activation and inhibition of the transient receptor potential vanilloid 4 (TRPV4) ion channel on intracranial pressure and CSF secretion rate. LPA-mediated modulation of TRPV4 was determined with electrophysiology and an ex vivo radio-isotope assay was employed to determine the effect of these modulators on choroid plexus transport.

Results

Elevated levels of LPA were observed in CSF obtained from patients with subarachnoid hemorrhage (SAH) and from rats with experimentally-inflicted intraventricular hemorrhage (IVH). Intraventricular administration of LPA caused elevated brain water content and ventriculomegaly in experimental rats, via its action as an agonist of the choroidal transient receptor potential vanilloid 4 (TRPV4) channel. TRPV4 was revealed as a novel regulator of ICP in experimental rats via its ability to modulate the CSF secretion rate through its direct activation of the Na⁺/K⁺/2Cl⁻ cotransporter (NKCC1) implicated in CSF secretion.

Conclusions

Together, our data reveal that a serum lipid present in brain pathologies with hemorrhagic events promotes CSF hypersecretion and ensuing brain water accumulation via its direct action on TRPV4 and its downstream regulation of NKCC1. TRPV4 may therefore be a promising future pharmacological target for pathologies involving brain water accumulation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12987-022-00361-9.

Membrane transporters control cerebrospinal fluid formation independently of conventional osmosis to modulate intracranial pressure

Background

Disturbances in the brain fluid balance can lead to life-threatening elevation in the intracranial pressure (ICP), which represents a vast clinical challenge. Nevertheless, the details underlying the molecular mechanisms governing cerebrospinal fluid (CSF) secretion are largely unresolved, thus preventing targeted and efficient pharmaceutical therapy of cerebral pathologies involving elevated ICP.

Methods

Experimental rats were employed for in vivo determinations of CSF secretion rates, ICP, blood pressure and ex vivo excised choroid plexus for morphological analysis and quantification of expression and activity of various transport proteins. CSF and blood extractions from rats, pigs, and humans were employed for osmolality determinations and a mathematical model employed to determine a contribution from potential local gradients at the surface of choroid plexus.

Results

We demonstrate that CSF secretion can occur independently of conventional osmosis and that local osmotic gradients do not suffice to support CSF secretion. Instead, the CSF secretion across the luminal membrane of choroid plexus relies approximately equally on the Na⁺/K⁺/2Cl⁻ cotransporter NKCC1, the Na⁺/HCO₃⁻ cotransporter NBCe2, and the Na⁺/K⁺-ATPase, but not on the Na⁺/H⁺ exchanger NHE1. We demonstrate that pharmacological modulation of CSF secretion directly affects the ICP.

Conclusions

CSF secretion appears to not rely on conventional osmosis, but rather occur by a concerted effort of different choroidal transporters, possibly via a molecular mode of water transport inherent in the proteins themselves. Therapeutic modulation of the rate of CSF secretion may be employed as a strategy to modulate ICP. These insights identify new promising therapeutic targets against brain pathologies associated with elevated ICP.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12987-022-00358-4.

The Mutual Influence of Predominant Microbes in Sourdough Fermentation: Focusing on Flavor Formation and Gene Transcription

The interplay between microorganisms generally plays a vital role in food fermentation. In this study, the mutual influence of Saccharomyces cerevisiae and Fructilactobacillus sanfranciscensis, the two predominant microbes in the sourdough ecosystem, were investigated in situ during fermentation. Doughs fermented with S. cerevisiae, F. sanfranciscensis, or their combination were compared regarding acid production, microbial density, and volatiles. Furthermore, in situ gene expressions were investigated using RNA-sequencing. The results showed that the presence of S. cerevisiae had no visible influence on F. sanfranciscensis, whereas F. sanfranciscensis facilitated the growth of S. cerevisiae but affected its volatile production since metabolites such as 3-methyl-1-butanol decreased. The RNA-sequencing demonstrated that S. cerevisiae significantly changed the gene transcripts implicated in amino acid metabolism in F. sanfranciscensis and may stimulate its growth suggested by the enrichment of the KEGG pathway of peptidoglycan biosynthesis.

Synthetic Essentiality of Tryptophan 2,3-Dioxygenase 2 in APC-Mutated Colorectal Cancer

Inactivation of adenomatous polyposis coli (APC) is common across many cancer types and serves as a critical initiating event in most sporadic colorectal cancers. APC deficiency activates WNT signaling, which remains an elusive target for cancer therapy, prompting us to apply the synthetic essentiality framework to identify druggable vulnerabilities for APC-deficient cancers. Tryptophan 2,3-dioxygenase 2 (TDO2) was identified as a synthetic essential effector of APC-deficient colorectal cancer. Mechanistically, APC deficiency results in the TCF4/β-catenin-mediated upregulation of TDO2 gene transcription. TDO2 in turn activates the Kyn-AhR pathway, which increases glycolysis to drive anabolic cancer cell growth and CXCL5 secretion to recruit macrophages into the tumor microenvironment. Therapeutically, APC-deficient colorectal cancer models were susceptible to TDO2 depletion or pharmacologic inhibition, which impaired cancer cell proliferation and enhanced antitumor immune profiles. Thus, APC deficiency activates a TCF4-TDO2-AhR-CXCL5 circuit that affects multiple cancer hallmarks via autonomous and nonautonomous mechanisms and illuminates a genotype-specific vulnerability in colorectal cancer.

SIGNIFICANCE

This study identifies critical effectors in the maintenance of APC-deficient colorectal cancer and demonstrates the relationship between APC/WNT pathway and kynurenine pathway signaling. It further determines the tumor-associated macrophage biology in APC-deficient colorectal cancer, informing genotype-specific therapeutic targets and the use of TDO2 inhibitors. This article is highlighted in the In This Issue feature, p. 1599.

Acetazolamide modulates intracranial pressure directly by its action on the cerebrospinal fluid secretion apparatus

Background

Elevated intracranial pressure (ICP) is observed in many neurological pathologies, e.g. hydrocephalus and stroke. This condition is routinely relieved with neurosurgical approaches, since effective and targeted pharmacological tools are still lacking. The carbonic anhydrase inhibitor, acetazolamide (AZE), may be employed to treat elevated ICP. However, its effectiveness is questioned, its location of action unresolved, and its tolerability low. Here, we determined the efficacy and mode of action of AZE in the rat .

Methods

We employed in vivo approaches including ICP and cerebrospinal fluid secretion measurements in anaesthetized rats and telemetric monitoring of ICP and blood pressure in awake rats in combination with ex vivo choroidal radioisotope flux assays and transcriptomic analysis.

Results

AZE effectively reduced the ICP, irrespective of the mode of drug administration and level of anaesthesia. The effect appeared to occur via a direct action on the choroid plexus and an associated decrease in cerebrospinal fluid secretion, and not indirectly via the systemic action of AZE on renal and vascular processes. Upon a single administration, the reduced ICP endured for approximately 10 h post-AZE delivery with no long-term changes of brain water content or choroidal transporter expression. However, a persistent reduction of ICP was secured with repeated AZE administrations throughout the day.

Conclusions

AZE lowers ICP directly via its ability to reduce the choroid plexus CSF secretion, irrespective of mode of drug administration.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12987-022-00348-6.

Transcriptional profiling of transport mechanisms and regulatory pathways in rat choroid plexus

BACKGROUND

Dysregulation of brain fluid homeostasis associates with brain pathologies in which fluid accumulation leads to elevated intracranial pressure. Surgical intervention remains standard care, since specific and efficient pharmacological treatment options are limited for pathologies with disturbed brain fluid homeostasis. Such lack of therapeutic targets originates, in part, from the incomplete map of the molecular mechanisms underlying cerebrospinal fluid (CSF) secretion by the choroid plexus.

METHODS

The transcriptomic profile of rat choroid plexus was generated by RNA Sequencing (RNAseq) of whole tissue and epithelial cells captured by fluorescence-activated cell sorting (FACS), and compared to proximal tubules. The bioinformatic analysis comprised mapping to reference genome followed by filtering for type, location, and association with alias and protein function. The transporters and associated regulatory modules were arranged in discovery tables according to their transcriptional abundance and tied together in association network analysis.

RESULTS

The transcriptomic profile of choroid plexus displays high similarity between sex and species (human, rat, and mouse) and lesser similarity to another high-capacity fluid-transporting epithelium, the proximal tubules. The discovery tables provide lists of transport mechanisms that could participate in CSF secretion and suggest regulatory candidates.

CONCLUSIONS

With quantification of the transport protein transcript abundance in choroid plexus and their potentially linked regulatory modules, we envision a molecular tool to devise rational hypotheses regarding future delineation of choroidal transport proteins involved in CSF secretion and their regulation. Our vision is to obtain future pharmaceutical targets towards modulation of CSF production in pathologies involving disturbed brain water dynamics.

KCNN4 is a Potential Biomarker for Predicting Cancer Prognosis and an Essential Molecule that Remodels Various Components in the Tumor Microenvironment: A Pan-Cancer Study

Objectives: Potassium Calcium-Activated Channel Subfamily N Member 4 (KCNN4) is a member of the KCNN family. Studies have revealed that KCNN4 is implicated in various physiological processes as well as promotes the malignant phenotypes of cancer cells. However, little is known about its associations with survival outcomes across varying cancer types.

Methods: Herein, we systematically explored the prognostic value of KCNN4 in the pan-cancer dataset retrieved from multiple databases. Next, we performed correlation analysis of KCNN4 expression with tumor mutational burden (TMB) and microsatellite instability (MSI), and immune checkpoint genes (ICGs) to assess its potential as a predictor of immunotherapy efficacy. Afterwards, patients were divided into increased-risk group and decreased-risk group based on the contrasting survival outcomes in various cancer types. Furthermore, the underlying mechanisms of the distinctive effects were analyzed using ESTIMATE, CIBERSORT algorithms, and Gene Set Enrichment Analysis (GSEA) analysis.

Results: KCNN4 expression levels were aberrant in transcriptomic and proteomic levels between cancer and normal control tissues in pan-cancer datasets, further survival analysis elucidated that KCNN4 expression was correlated to multiple survival data, and clinical annotations. Besides, KCNN4 expression was correlated to TMB and MSI levels in 14 types and 12 types of pan-cancers, respectively. Meanwhile, different types of cancer have specific tumor-infiltrating immune cell (TICs) profiles.

Conclusions: Our results revealed that KCNN4 could be an essential biomarker for remodeling components in the tumor microenvironment (TME), and a robust indicator for predicting prognosis as well as immunotherapy response in pan-cancer patients.

Research perspectives-Pipelines to human tendon transcriptomics

Tendon transcriptomics is a rapidly growing field in musculoskeletal biology. The ultimate aim of many current tendon transcriptomic studies is characterization of in vitro, ex vivo, or in vivo, healthy, and diseased tendon microenvironments to identify the underlying pathways driving human tendon pathology. The transcriptome interfaces between genomic, proteomic, and metabolomic signatures of the tendon cellular niche and the response of this niche to stimuli. Some of the greatest bottlenecks in tendon transcriptomics relate to the availability and quality of human tendon tissue, hence animal tissues are frequently used even though human tissue is most translationally relevant. Here, we review the variability associated with human donor and procurement factors, such as whether the tendon is cadaveric or a clinical remnant, and how these variables affect the quality and relevance of the transcriptomes obtained. Moreover, age, sex, and health demographic variables impact the human tendon transcriptome. Tendons present tissue-specific challenges for cell, nuclei, and RNA extraction that include a dense extracellular matrix, low cellularity, and therefore low RNA yield of variable quality. Consideration of these factors is particularly important for single-cell and single-nuclei resolution transcriptomics due to the necessity for unbiased and representative cell or nuclei populations. Different cell, nuclei, and RNA extraction methods, library preparation, and quality control methods are used by the tendon research community and attention should be paid to these when designing and reporting studies. We discuss the different components and challenges of human tendon transcriptomics, and propose pipelines, quality control, and reporting guidelines for future work in the field.

OBIF: an omics-based interaction framework to reveal molecular drivers of synergy

Bioactive molecule library screening may empirically identify effective combination therapies, but molecular mechanisms underlying favorable drug–drug interactions often remain unclear, precluding further rational design. In the absence of an accepted systems theory to interrogate synergistic responses, we introduce Omics-Based Interaction Framework (OBIF) to reveal molecular drivers of synergy through integration of statistical and biological interactions in synergistic biological responses. OBIF performs full factorial analysis of feature expression data from single versus dual exposures to identify molecular clusters that reveal synergy-mediating pathways, functions and regulators. As a practical demonstration, OBIF analyzed transcriptomic and proteomic data of a dyad of immunostimulatory molecules that induces synergistic protection against influenza A and revealed unanticipated NF-κB/AP-1 cooperation that is required for antiviral protection. To demonstrate generalizability, OBIF analyzed data from a diverse array of Omics platforms and experimental conditions, successfully identifying the molecular clusters driving their synergistic responses. Hence, unlike existing synergy quantification and prediction methods, OBIF is a phenotype-driven systems model that supports multiplatform interrogation of synergy mechanisms.

Pancreatic Ductal Adenocarcinoma (PDAC) circulating tumor cells influence myeloid cell differentiation to support their survival and immunoresistance in portal vein circulation

The portal venous circulation provides a conduit for pancreatic ductal adenocarcinoma (PDAC) tumor cells to the liver parenchyma sinusoids, a frequent site of metastasis. Turbulent flow in the portal circulation promotes retention of PDAC shed circulating tumor cells (CTC) and myeloid-derived immunosuppressor cells (MDSC). Excessive colony stimulating factor-1 receptor (CSF1R) signaling can induce myeloid differentiation to MDSC and transformation of MDSC to myeloid-derived fibroblasts (M-FB). Interactions between PDAC CTC and M-FB in the portal blood promotes the formation of immunoresistant clusters that enhance CTC proliferation, migration, and survival. Analysis of portal and peripheral blood samples collected intraoperatively from 30 PDAC patients undergoing pancreatico-duodenectomy showed that PDAC patient plasma contained high levels of macrophage colony stimulating factor (M-CSF/CSF1), granulocyte-macrophage colony stimulating factor (GM-CSF/CSF2), interleukin-8 (IL-8), and interleukin-34 (IL-34) compared to healthy control levels. Moreover, the level of M-CSF in portal blood was significantly higher than that detected in the peripheral blood of PDAC patients. PDAC CTC aseptically isolated by fluorescence activated cell sorting (FACS) out of freshly collected patient portal blood mononuclear cells (PortalBMC) had elevated RNA expression of IL34 (IL-34 gene) and CSF1 (M-CSF/CSF1 gene) which both signal through CSF1R. PDAC CTC also had high levels of RNA expression for CXCL8, the gene encoding chemokine interleukin-8 (IL-8) which can attract myeloid cells through their CXCR2 receptors. FACS-isolated portal PDAC CTC and M-FB co-cultured ex vivo had increased CTC proliferation, motility, and cluster formation compared to CTC cultured alone. CSF1R and CXCR2 cell surface expression were found on PDAC portal blood CTC and M-FB, suggesting that both cell types may respond to M-CSF, IL-34, and IL-8-mediated signaling. Portal PDAC CTC displayed enhanced RNA expression of CSF1 and IL34, while CTC+M-FB+ clusters formed in vivo had increased RNA expression of CSF2 and IL34. Portal M-FB were found to have high CSF1R RNA expression. CTC isolated from ex vivo 7-day cultures of PDAC patient portal blood mononuclear cells (PortalBMC) expressed elevated CSF1, IL34, and IL8 RNA, and CSF1 expression was elevated in M-FB. Treatment with rabbit anti-CSF1R antibodies decreased CTC proliferation. Treatment of PortalBMC cultures with humanized anti-CSF1R, humanized anti-IL-8, or anti-IL-34 antibodies disrupted CTC cluster formation and increased CTC apoptosis. U937 myeloid precursor cell line cultures treated with conditioned media from PortalBMC ex vivo cultures without treatment or treated with anti-IL-8 and/or anti-CSF1R did not prevent myeloid differentiation in the myeloid precursor cell line U937 to macrophage, dendritic cell, MDSC, and M-FB phenotypes; whereas, U937 cultures treated with conditioned media from PortalBMC ex vivo cultures exposed to anti-IL-34 were significantly inhibited in their myeloid differentiation to all but the M-FB phenotype. PDAC patient T cells that were found phenotypically anergic (CD3+CD25+CTLA4+PD1L1+) in PortalBMC could be re-activated (CD3+CD25+CTLA4-PD1L1-), and displayed increased interferon gamma (IFNγ) production when PortalBMC ex vivo cultures were treated with anti-CSF1R, anti-IL-8, and anti-IL-34 antibodies alone or in combination. These findings suggest that PDAC CTC have the potential to influence myeloid differentiation and/or antigen presenting cell activation in the PDAC portal blood microenvironment, and that disruption of CTC/M-FB interactions may be potential targets for reversing the immunosuppression supporting CTC survival in the portal blood.

Alternative polyadenylation utilization results in ribosome assembly and mRNA translation deficiencies in a model for muscle aging

Aging-associated muscle wasting is regulated by multiple molecular processes, whereby aberrant mRNA processing regulation induces muscle wasting. The poly(A)-binding protein nuclear 1 (PABPN1) regulates polyadenylation site (PAS) utilization, in the absence of PABPN1 the alternative PAS (APA) is utilized. Reduced PABPN1 levels induce muscle wasting where the expression of cellular processes regulating protein homeostasis, the ubiquitin-proteasome system, and translation, are robustly dysregulated. Translation is impacted by mRNA levels, but PABPN1 impact on translation is not fully understood. Here we show that a persistent reduction in PABPN1 levels led to a significant loss of translation efficiency. RNA sequencing of rRNA-depleted libraries from polysome traces revealed reduced mRNA abundance across ribosomal fractions, as well as reduced levels of small RNAs. We show that the abundance of translated mRNAs in the polysomes correlated with PAS switches at the 3'-UTR. Those mRNAs are enriched in cellular processes that are essential for proper muscle function. This study suggests that the effect of PABPN1 on translation efficiency impacts protein homeostasis in aging-associated muscle atrophy.

LncRNA Biomarkers of Inflammation and Cancer

Long noncoding RNAs (lncRNAs) are promising candidates as biomarkers of inflammation and cancer. LncRNAs have several properties that make them well-suited as molecular markers of disease: (1) many lncRNAs are expressed in a tissue-specific manner, (2) distinct lncRNAs are upregulated based on different inflammatory or oncogenic stimuli, (3) lncRNAs released from cells are packaged and protected in extracellular vesicles, and (4) circulating lncRNAs in the blood are detectable using various RNA sequencing approaches. Here we focus on the potential for lncRNA biomarkers to detect inflammation and cancer, highlighting key biological, technological, and analytical considerations that will help advance the development of lncRNA-based liquid biopsies.

Hormone and carbohydrate metabolism associated genes play important roles in rhizome bud full-year germination of Cephalostachyum pingbianense

Cephalostachyum pingbianense is the only woody bamboo species that can produce bamboo shoots in four seasons under natural conditions. So far, the regulatory mechanism of shoot bud differentiation and development is unknown. In the present study, indole-3-acetic acid (IAA), zeatin riboside (ZR), gibberellin A3 (GA₃ ) and abscisic acid (ABA) contents determination, RNA sequencing and differentially expressed gene analysis were performed on dormant rhizome bud (DR), growing rhizome bud (GR), and germinative bud (GB) in each season. The results showed that the contents of IAA and ZR increased while ABA content decreased, and GA₃ content was stable during bud transition from dormancy to germination in each season. Moreover, rhizome bud germination was cooperatively regulated by multiple pathways such as carbohydrate metabolism, hormone signal transduction, cell wall biogenesis, temperature response, and water transport. The inferred hub genes among these candidates were identified by protein-protein interaction network analyses, most of which were involved in hormone and carbohydrate metabolism, such as HK and BGLU4 in spring, IDH and GH3 in winter, GPI and talA/talB in summer and autumn. It is speculated that dynamic phytohormone changes and differential expression of these genes promote the release of rhizome bud dormancy and contribute to the phenological characteristics of full-year shooting. Moreover, the rhizome buds of C. pingbianense may not suffer from ecodormancy in winter. These findings would help accumulate knowledge on shooting mechanisms in woody bamboos and provide a physiological insight into germplasm conservation and forest management of C. pingbianense.

Exosomal circLPAR1 functions in colorectal cancer diagnosis and tumorigenesis through suppressing BRD4 via METTL3–eIF3h interaction

Background

Exosomes have emerged as vital biomarkers of multiple cancers and contain abundant circular RNAs (circRNAs). However, the potential for exosomal circRNAs to be used in diagnostics and their molecular mechanism of action in colorectal cancer (CRC) remain unclear.

Methods

CRC-specific exosomal circRNAs were identified by RNA sequencing, exoRBase database and a tissue microarray. The diagnostic performance of plasma exosomal circRNAs was evaluated among cancer-free controls, precancer individuals, CRC patients, and patients with other types of cancer. The corresponding biological functions were mainly assessed using circRNA pull-down, proteomic analysis, and RNA immunoprecipitation assay underlying cellular and mouse models.

Results

CircLPAR1 was encapsulated in exosomes with high stability and detectability, and its expression in plasma exosomes was remarkably decreased during CRC development but recovered after surgery. Exosomal circLPAR1 showed cancer specificity in CRC diagnosis and increased the diagnostic performance to an area under the receiver operating characteristic curve of 0.875, as determined by analysing its performance in combination with common clinical biomarkers CEA and CA19–9. Additionally, circLPAR1 was downregulated in CRC tissues and was associated with overall survival. Mechanistically, exosomal circLPAR1 was internalized by CRC cells, and it suppressed tumor growth, likely because exosomal circLPAR1 directly bound with eIF3h specifically suppressed the METTL3-eIF3h interaction, decreasing the translation of oncogene BRD4.

Conclusions

This comprehensive study highlights plasma exosomal circLPAR1 as a promising predictor in CRC diagnosis and describes its biological regulation of colorectal tumorigenesis. This study provides a new perspective on early diagnosis in the clinic and pathogenesis in disease development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12943-021-01471-y.

Gene expression profiling reveals transcription factor networks and subgenome bias during Brassica napus seed development

We profiled the global gene expression landscape across the reproductive lifecycle of Brassica napus. Comparative analysis of this nascent amphidiploid revealed the contribution of each subgenome to plant reproduction. Whole-genome transcription factor networks identified BZIP11 as a transcriptional regulator of early B. napus seed development. Knockdown of BZIP11 using RNA interference resulted in a similar reduction in gene activity of predicted gene targets, and a reproductive-lethal phenotype. Global mRNA profiling revealed lower accumulation of Cⁿ subgenome transcripts relative to the Aⁿ subgenome. Subgenome-specific transcription factor networks identified distinct transcription factor families enriched in each of the Aⁿ and Cⁿ subgenomes early in seed development. Analysis of laser-microdissected seed subregions further reveal subgenome expression dynamics in the embryo, endosperm and seed coat of early stage seeds. Transcription factors predicted to be regulators encoded by the Aⁿ subgenome are expressed primarily in the seed coat, whereas regulators encoded by the Cⁿ subgenome were expressed primarily in the embryo. Data suggest subgenome bias are characteristic features of the B. napus seed throughout development, and that such bias might not be universal across the embryo, endosperm and seed coat of the developing seed. Transcriptional networks spanning both the Aⁿ and Cⁿ genomes of the whole B. napus seed can identify valuable targets for seed development research and that -omics level approaches to studying gene regulation in B. napus can benefit from both broad and high-resolution analyses.

A robust biostatistical method leverages informative but uncertainly determined qPCR data for biomarker detection, early diagnosis, and treatment

As a common medium-throughput technique, qPCR (quantitative real-time polymerase chain reaction) is widely used to measure levels of nucleic acids. In addition to accurate and complete data, experimenters have unavoidably observed some incomplete and uncertainly determined qPCR data because of intrinsically low overall amounts of biological materials, such as nucleic acids present in biofluids. When there are samples with uncertainly determined qPCR data, some investigators apply the statistical complete-case method by excluding the subset of samples with uncertainly determined data from analysis (CO), while others simply choose not to analyze (CNA) these datasets altogether. To include as many observations as possible in analysis for interesting differential changes between groups, some investigators set incomplete observations equal to the maximum quality qPCR cycle (MC), such as 32 and 40. Although straightforward, these methods may decrease the sample size, skew the data distribution, and compromise statistical power and research reproducibility across replicate qPCR studies. To overcome the shortcomings of the existing, commonly-used qPCR data analysis methods and to join the efforts in advancing statistical analysis in rigorous preclinical research, we propose a robust nonparametric statistical cycle-to-threshold method (CTOT) to analyze incomplete qPCR data for two-group comparisons. CTOT incorporates important characteristics of qPCR data and time-to-event statistical methodology, resulting in a novel analytical method for qPCR data that is built around good quality data from all subjects, certainly determined or not. Considering the benchmark full data (BFD), we compared the abilities of CTOT, CO, MC, and CNA statistical methods to detect interesting differential changes between groups with informative but uncertainly determined qPCR data. Our simulations and applications show that CTOT improves the power of detecting and confirming differential changes in many situations over the three commonly used methods without excess type I errors. The robust nonparametric statistical method of CTOT helps leverage qPCR technology and increase the power to detect differential changes that may assist decision making with respect to biomarker detection and early diagnosis, with the goal of improving the management of patient healthcare.

Comparative transcriptomics reveal tissue level specialization towards diet in prickleback fishes

Beyond a few obvious examples (e.g., gut length, amylase activity), digestive and metabolic specializations towards diet remain elusive in fishes. Thus, we compared gut length, δ¹³C and δ¹⁵N signatures of the liver, and expressed genes in the intestine and liver of wild-caught individuals of four closely-related, sympatric prickleback species (family Stichaeidae) with different diets: Xiphister mucosus (herbivore), its sister taxon X. atropurpureus (omnivore), Phytichthys chirus (omnivore) and the carnivorous Anoplarchus purpurescens. We also measured the same parameters after feeding them carnivore or omnivore diets in the laboratory for 4 weeks. Growth and isotopic signatures showed assimilation of the laboratory diets, and gut length was significantly longer in X. mucosus in comparison to the other fishes, whether in the wild, or in the lab consuming the different diets. Dozens of genes relating to digestion and metabolism were observed to be under selection in the various species, but P. chirus stood out with some genes in the liver showing strong positive selection, and these genes correlating with differing isotopic incorporation of the laboratory carnivore diet in this species. Although the intestine showed variation in the expression of hundreds of genes in response to the laboratory diets, the liver exhibited species-specific gene expression patterns that changed very little (generally <40 genes changing expression, with P. chirus providing an exception). Overall, our results suggest that the intestine is plastic in function, but the liver may be where specialization manifests since this tissue shows species-specific gene expression patterns that match with natural diet.

Elevated CSF inflammatory markers in patients with idiopathic normal pressure hydrocephalus do not promote NKCC1 hyperactivity in rat choroid plexus

BACKGROUND

Idiopathic normal pressure hydrocephalus (iNPH) is a potentially reversible neurological condition of unresolved etiology characterized by a clinical triad of symptoms; gait disturbances, urinary incontinence, and cognitive deterioration. In the present study, we aimed to elucidate the molecular coupling between inflammatory markers and development of iNPH and determine whether inflammation-induced hyperactivity of the choroidal Na⁺/K⁺/2Cl^- cotransporter (NKCC1) that is involved in cerebrospinal fluid (CSF) secretion could contribute to the iNPH pathogenesis.

METHODS

Lumbar CSF samples from 20 iNPH patients (10 with clinical improvement upon CSF shunting, 10 without clinical improvement) and 20 elderly control subjects were analyzed with the novel proximity extension assay technique for presence of 92 different inflammatory markers. RNA-sequencing was employed to delineate choroidal abundance of the receptors for the inflammatory markers found elevated in the CSF from iNPH patients. The ability of the elevated inflammatory markers to modulate choroidal NKCC1 activity was determined by addition of combinations of rat version of these in ex vivo experiments on rat choroid plexus.

RESULTS

11 inflammatory markers were significantly elevated in the CSF from iNPH patients compared to elderly control subjects: CCL28, CCL23, CCL3, OPG, CXCL1, IL-18, IL-8, OSM, 4E-BP1, CXCL6, and Flt3L. One inflammatory marker, CDCP1, was significantly decreased in iNPH patients compared to control subjects. None of the inflammatory markers differed significantly when comparing iNPH patients with and without clinical improvement upon CSF shunting. All receptors for the elevated inflammatory markers were expressed in the rat and human choroid plexus, except CCR4 and CXCR1, which were absent from the rat choroid plexus. None of the elevated inflammatory markers found in the CSF from iNPH patients modulated the choroidal NKCC1 activity in ex vivo experiments on rat choroid plexus.

CONCLUSION

The CSF from iNPH patients contains elevated levels of a subset of inflammatory markers. Although the corresponding inflammatory receptors are, in general, expressed in the choroid plexus of rats and humans, their activation did not modulate the NKCC1-mediated fraction of choroidal CSF secretion ex vivo. The molecular mechanisms underlying ventriculomegaly in iNPH, and the possible connection to inflammation, therefore remains to be elucidated.

RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

Background

Heart failure (HF) is one of the most common complications of cardiovascular diseases (CVDs) and among the leading causes of death in the US. Many other CVDs can lead to increased mortality as well. Investigating the genetic epidemiology and susceptibility to CVDs is a central focus of cardiology and biomedical life sciences. Several studies have explored expression of key CVD genes specially in HF, yet new targets and biomarkers for early diagnosis are still missing to support personalized treatment. Lack of gender-specific cardiac biomarker thresholds in men and women may be the reason for CVD underdiagnosis in women, and potentially increased morbidity and mortality as a result, or conversely, an overdiagnosis in men. In this context, it is important to analyze the expression and enrichment of genes with associated phenotypes and disease-causing variants among high-risk CVD populations.

Methods

We performed RNA sequencing focusing on key CVD genes with a great number of genetic associations to HF. Peripheral blood samples were collected from a broad age range of adult male and female CVD patients. These patients were clinically diagnosed with CVDs and CMS/HCC HF, as well as including cardiomyopathy, hypertension, obesity, diabetes, asthma, high cholesterol, hernia, chronic kidney, joint pain, dizziness and giddiness, osteopenia of multiple sites, chest pain, osteoarthritis, and other diseases.

Results

We report RNA-seq driven case–control study to analyze patterns of expression in genes and differentiating the pathways, which differ between healthy and diseased patients. Our in-depth gene expression and enrichment analysis of RNA-seq data from patients with mostly HF and other CVDs on differentially expressed genes and CVD annotated genes revealed 4,885 differentially expressed genes (DEGs) and regulation of 41 genes known for HF and 23 genes related to other CVDs, with 15 DEGs as significantly expressed including four genes already known (FLNA, CST3, LGALS3, and HBA1) for HF and CVDs with the enrichment of many pathways. Furthermore, gender and ethnic group specific analysis showed shared and unique genes between the genders, and among different races. Broadening the scope of the results in clinical settings, we have linked the CVD genes with ICD codes.

Conclusions

Many pathways were found to be enriched, and gender-specific analysis showed shared and unique genes between the genders. Additional testing of these genes may lead to the development of new clinical tools to improve diagnosis and prognosis of CVD patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-021-00367-8.

E. coli enhance colonization resistance against Salmonella Typhimurium by competing for galactitol, a context-dependent limiting carbon source

The composition of intrinsic microbial communities determines if invading pathogens will find a suitable niche for colonization and cause infection or be eliminated. Here, we investigate how commensal E. coli mediate colonization resistance (CR) against Salmonella Typhimurium (S. Tm). Using synthetic bacterial communities, we show that the capacity of E. coli Mt1B1 to block S. Tm colonization depends on the microbial context. In an infection-permissive context, E. coli utilized a high diversity of carbon sources and was unable to block S. Tm invasion. In mice that were stably colonized by twelve phylogenetically diverse murine gut bacteria (OMM¹²), establishing a protective context, E. coli depleted galactitol, a substrate otherwise fueling S. Tm colonization. Here, Lachnospiraceae, capable of consuming C5 and C6 sugars, critically contributed to CR. We propose that E. coli provides CR by depleting a limited carbon source when in a microbial community adept at removing simple sugars from the intestine.

cdev: a ground-truth based measure to evaluate RNA-seq normalization performance

Normalization of RNA-seq data has been an active area of research since the problem was first recognized a decade ago. Despite the active development of new normalizers, their performance measures have been given little attention. To evaluate normalizers, researchers have been relying on ad hoc measures, most of which are either qualitative, potentially biased, or easily confounded by parametric choices of downstream analysis. We propose a metric called condition-number based deviation, or cdev, to quantify normalization success. cdev measures how much an expression matrix differs from another. If a ground truth normalization is given, cdev can then be used to evaluate the performance of normalizers. To establish experimental ground truth, we compiled an extensive set of public RNA-seq assays with external spike-ins. This data collection, together with cdev, provides a valuable toolset for benchmarking new and existing normalization methods.

Accelerating precision anti-cancer therapy by time-lapse and label-free 3D tumor slice culture platform

The feasibility of personalized medicine for cancer treatment is largely hampered by costly, labor-intensive and time-consuming models for drug discovery. Herein, establishing new pre-clinical models to tackle these issues for personalized medicine is urgently demanded.

Methods: We established a three-dimensional tumor slice culture (3D-TSC) platform incorporating label-free techniques for time-course experiments to predict anti-cancer drug efficacy and validated the 3D-TSC model by multiphoton fluorescence microscopy, RNA sequence analysis, histochemical and histological analysis.

Results: Using time-lapse imaging of the apoptotic reporter sensor C3 (C3), we performed cell-based high-throughput drug screening and shortlisted high-efficacy drugs to screen murine and human 3D-TSCs, which validate effective candidates within 7 days of surgery. Histological and RNA sequence analyses demonstrated that 3D-TSCs accurately preserved immune components of the original tumor, which enables the successful achievement of immune checkpoint blockade assays with antibodies against PD-1 and/or PD-L1. Label-free multiphoton fluorescence imaging revealed that 3D-TSCs exhibit lipofuscin autofluorescence features in the time-course monitoring of drug response and efficacy.

Conclusion: This technology accelerates precision anti-cancer therapy by providing a cheap, fast, and easy platform for anti-cancer drug discovery.

Assessment of reference genes at six different developmental stages of Schistosoma mansoni for quantitative RT-PCR

Reverse-transcription quantitative real-time polymerase chain reaction (RT-qPCR) is the most used, fast, and reproducible method to confirm large-scale gene expression data. The use of stable reference genes for the normalization of RT-qPCR assays is recognized worldwide. No systematic study for selecting appropriate reference genes for usage in RT-qPCR experiments comparing gene expression levels at different Schistosoma mansoni life-cycle stages has been performed. Most studies rely on genes commonly used in other organisms, such as actin, tubulin, and GAPDH. Therefore, the present study focused on identifying reference genes suitable for RT-qPCR assays across six S. mansoni developmental stages. The expression levels of 25 novel candidates that we selected based on the analysis of public RNA-Seq datasets, along with eight commonly used reference genes, were systematically tested by RT-qPCR across six developmental stages of S. mansoni (eggs, miracidia, cercariae, schistosomula, adult males and adult females). The stability of genes was evaluated with geNorm, NormFinder and RefFinder algorithms. The least stable candidate reference genes tested were actin, tubulin and GAPDH. The two most stable reference genes suitable for RT-qPCR normalization were Smp_101310 (Histone H4 transcription factor) and Smp_196510 (Ubiquitin recognition factor in ER-associated degradation protein 1). Performance of these two genes as normalizers was successfully evaluated with females maintained unpaired or paired to males in culture for 8 days, or with worm pairs exposed for 16 days to double-stranded RNAs to silence a protein-coding gene. This study provides reliable reference genes for RT-qPCR analysis using samples from six different S. mansoni life-cycle stages.

Hypoxic mesenchymal stem cells ameliorate acute kidney ischemia-reperfusion injury via enhancing renal tubular autophagy

BACKGROUND

Acute kidney injury (AKI) is an emerging global healthcare issue without effective therapy yet. Autophagy recycles damaged organelles and helps maintain tissue homeostasis in acute renal ischemia-reperfusion (I/R) injury. Hypoxic mesenchymal stem cells (HMSCs) represent an innovative cell-based therapy in AKI. Moreover, the conditioned medium of HMSCs (HMSC-CM) rich in beneficial trophic factors may serve as a cell-free alternative therapy. Nonetheless, whether HMSCs or HMSC-CM mitigate renal I/R injury via modulating tubular autophagy remains unclear.

METHODS

Renal I/R injury was induced by clamping of the left renal artery with right nephrectomy in male Sprague-Dawley rats. The rats were injected with either PBS, HMSCs, or HMSC-CM immediately after the surgery and sacrificed 48 h later. Renal tubular NRK-52E cells subjected to hypoxia-reoxygenation (H/R) injury were co-cultured with HMSCs or treated with HMSC-CM to assess the regulatory effects of HSMCs on tubular autophagy and apoptosis. The association of tubular autophagy gene expression and renal recovery was also investigated in patients with ischemic AKI.

RESULT

HMSCs had a superior anti-oxidative effect in I/R-injured rat kidneys as compared to normoxia-cultured mesenchymal stem cells. HMSCs further attenuated renal macrophage infiltration and inflammation, reduced tubular apoptosis, enhanced tubular proliferation, and improved kidney function decline in rats with renal I/R injury. Moreover, HMSCs suppressed superoxide formation, reduced DNA damage and lipid peroxidation, and increased anti-oxidants expression in renal tubular epithelial cells during I/R injury. Co-culture of HMSCs with H/R-injured NRK-52E cells also lessened tubular cell death. Mechanistically, HMSCs downregulated the expression of pro-inflammatory interleukin-1β, proapoptotic Bax, and caspase 3. Notably, HMSCs also upregulated the expression of autophagy-related LC3B, Atg5 and Beclin 1 in renal tubular cells both in vivo and in vitro. Addition of 3-methyladenine suppressed the activity of autophagy and abrogated the renoprotective effects of HMSCs. The renoprotective effect of tubular autophagy was further validated in patients with ischemic AKI. AKI patients with higher renal LC3B expression were associated with better renal recovery.

CONCLUSION

The present study describes that the enhancing effect of MSCs, and especially of HMCSs, on tissue autophagy can be applied to suppress renal tubular apoptosis and attenuate renal impairment during renal I/R injury in the rat. Our findings provide further mechanistic support to HMSCs therapy and its investigation in clinical trials of ischemic AKI.

TPM, FPKM, or Normalized Counts? A Comparative Study of Quantification Measures for the Analysis of RNA-seq Data from the NCI Patient-Derived Models Repository

Background

In order to correctly decode phenotypic information from RNA-sequencing (RNA-seq) data, careful selection of the RNA-seq quantification measure is critical for inter-sample comparisons and for downstream analyses, such as differential gene expression between two or more conditions. Several methods have been proposed and continue to be used. However, a consensus has not been reached regarding the best gene expression quantification method for RNA-seq data analysis.

Methods

In the present study, we used replicate samples from each of 20 patient-derived xenograft (PDX) models spanning 15 tumor types, for a total of 61 human tumor xenograft samples available through the NCI patient-derived model repository (PDMR). We compared the reproducibility across replicate samples based on TPM (transcripts per million), FPKM (fragments per kilobase of transcript per million fragments mapped), and normalized counts using coefficient of variation, intraclass correlation coefficient, and cluster analysis.

Results

Our results revealed that hierarchical clustering on normalized count data tended to group replicate samples from the same PDX model together more accurately than TPM and FPKM data. Furthermore, normalized count data were observed to have the lowest median coefficient of variation (CV), and highest intraclass correlation (ICC) values across all replicate samples from the same model and for the same gene across all PDX models compared to TPM and FPKM data.

Conclusion

We provided compelling evidence for a preferred quantification measure to conduct downstream analyses of PDX RNA-seq data. To our knowledge, this is the first comparative study of RNA-seq data quantification measures conducted on PDX models, which are known to be inherently more variable than cell line models. Our findings are consistent with what others have shown for human tumors and cell lines and add further support to the thesis that normalized counts are the best choice for the analysis of RNA-seq data across samples.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02936-w.

Shotgun metagenomics reveals distinct functional diversity and metabolic capabilities between 12 000-year-old permafrost and active layers on Muot da Barba Peider (Swiss Alps)

The warming-induced thawing of permafrost promotes microbial activity, often resulting in enhanced greenhouse gas emissions. The ability of permafrost microorganisms to survive the in situ sub-zero temperatures, their energetic strategies and their metabolic versatility in using soil organic materials determine their growth and functionality upon thawing. Hence, functional characterization of the permafrost microbiome, particularly in the underexplored mid-latitudinal alpine regions, is a crucial first step in predicting its responses to the changing climate, and the consequences for soil-climate feedbacks. In this study, for the first time, the functional potential and metabolic capabilities of a temperate mountain permafrost microbiome from central Europe has been analysed using shotgun metagenomics. Permafrost and active layers from the summit of Muot da Barba Peider (MBP) [Swiss Alps, 2979 m above sea level (a.s.l.)] revealed a strikingly high functional diversity in the permafrost (north-facing soils at a depth of 160 cm). Permafrost metagenomes were enriched in stress-response genes (e.g. cold-shock genes, chaperones), as well as in genes involved in cell defence and competition (e.g. antiviral proteins, antibiotics, motility, nutrient-uptake ABC transporters), compared with active-layer metagenomes. Permafrost also showed a higher potential for the synthesis of carbohydrate-active enzymes, and an overrepresentation of genes involved in fermentation, carbon fixation, denitrification and nitrogen reduction reactions. Collectively, these findings demonstrate the potential capabilities of permafrost microorganisms to thrive in cold and oligotrophic conditions, and highlight their metabolic versatility in carbon and nitrogen cycling. Our study provides a first insight into the high functional gene diversity of the central European mountain permafrost microbiome. Our findings extend our understanding of the microbial ecology of permafrost and represent a baseline for future investigations comparing the functional profiles of permafrost microbial communities at different latitudes.

ATP signaling in the integrative neural center of Aplysia californica

ATP and its ionotropic P2X receptors are components of the most ancient signaling system. However, little is known about the distribution and function of purinergic transmission in invertebrates. Here, we cloned, expressed, and pharmacologically characterized the P2X receptors in the sea slug Aplysia californica—a prominent neuroscience model. AcP2X receptors were successfully expressed in Xenopus oocytes and displayed activation by ATP with two-phased kinetics and Na⁺-dependence. Pharmacologically, they were different from other P2X receptors. The ATP analog, Bz-ATP, was a less effective agonist than ATP, and PPADS was a more potent inhibitor of the AcP2X receptors than the suramin. AcP2X were uniquely expressed within the cerebral F-cluster, the multifunctional integrative neurosecretory center. AcP2X receptors were also detected in the chemosensory structures and the early cleavage stages. Therefore, in molluscs, rapid ATP-dependent signaling can be implicated both in development and diverse homeostatic functions. Furthermore, this study illuminates novel cellular and systemic features of P2X-type ligand-gated ion channels for deciphering the evolution of neurotransmitters.

Mutation of the Cell Cycle Regulator p27kip1 Drives Pseudohypoxic Pheochromocytoma Development

Simple Summary

Pheochromocytomas and paragangliomas (PPGLs) can be subdivided into at least three different subgroups associated with different clinical manifestations and depending on the risk to metastasize. A shortage in human tumor material, the lack of a functional human cell line and very limited animal models were major drawbacks for PPGL research and consequently for the development of patient-tailored targeted therapies. We have previously reported that the MENX rat model develops pheochromocytoma with a full penetrance at the age of 8–10 months, however, it was unclear which human group the rat tumors modeled best. In order to characterize the rat pheochromocytomas, we analyzed gene expression, the catecholamine profile, TCA-cycle metabolism, methylation, angiogenesis, histology and mitochondrial ultrastructure. In all aspects, rat MENX pheochromocytomas resemble the features of the human pseudohypoxia group, the most aggressive one and in need of effective therapeutic approaches.

Abstract

Background: Pseudohypoxic tumors activate pro-oncogenic pathways typically associated with severe hypoxia even when sufficient oxygen is present, leading to highly aggressive tumors. Prime examples are pseudohypoxic pheochromocytomas and paragangliomas (p-PPGLs), neuroendendocrine tumors currently lacking effective therapy. Previous attempts to generate mouse models for p-PPGLs all failed. Here, we describe that the rat MENX line, carrying a Cdkn1b (p27) frameshift-mutation, spontaneously develops pseudohypoxic pheochromocytoma (p-PCC). Methods: We compared rat p-PCCs with their cognate human tumors at different levels: histology, immunohistochemistry, catecholamine profiling, electron microscopy, transcriptome and metabolome. The vessel architecture and angiogenic potential of pheochromocytomas (PCCs) was analyzed by light-sheet fluorescence microscopy ex vivo and multi-spectral optoacoustic tomography (MSOT) in vivo. Results: The analysis of tissues at various stages, from hyperplasia to advanced grades, allowed us to correlate tumor characteristics with progression. Pathological changes affecting the mitochrondrial ultrastructure where present already in hyperplasias. Rat PCCs secreted high levels of norepinephrine and dopamine. Transcriptomic and metabolomic analysis revealed changes in oxidative phosphorylation that aggravated over time, leading to an accumulation of the oncometabolite 2-hydroxyglutarate, and to hypermethylation, evident by the loss of the epigenetic mark 5-hmC. While rat PCC xenografts showed high oxygenation, induced by massive neoangiogenesis, rat primary PCC transcriptomes possessed a pseudohypoxic signature of high Hif2a, Vegfa, and low Pnmt expression, thereby clustering with human p-PPGL. Conclusion: Endogenous rat PCCs recapitulate key phenotypic features of human p-PPGLs. Thus, MENX rats emerge as the best available animal model of these aggressive tumors. Our study provides evidence of a link between cell cycle dysregulation and pseudohypoxia.

EXO70A2 Is Critical for Exocyst Complex Function in Pollen Development

Pollen development, pollen grain germination, and pollen tube elongation are crucial biological processes in angiosperm plants that need precise regulation to deliver sperm cells to ovules for fertilization. Highly polarized secretion at a growing pollen tube tip requires the exocyst tethering complex responsible for specific targeting of secretory vesicles to the plasma membrane. Here, we demonstrate that Arabidopsis (Arabidopsis thaliana) EXO70A2 (At5g52340) is the main exocyst EXO70 isoform in the male gametophyte, governing the conventional secretory function of the exocyst, analogous to EXO70A1 (At5g03540) in the sporophyte. Our analysis of a CRISPR-generated exo70a2 mutant revealed that EXO70A2 is essential for efficient pollen maturation, pollen grain germination, and pollen tube growth. GFP:EXO70A2 was localized to the nucleus and cytoplasm in developing pollen grains and later to the apical domain in growing pollen tube tips characterized by intensive exocytosis. Moreover, EXO70A2 could substitute for EXO70A1 function in the sporophyte, but not vice versa, indicating partial functional redundancy of these two closely related isoforms and higher specificity of EXO70A2 for pollen development-related processes. Phylogenetic analysis revealed that the ancient duplication of EXO70A, one of which is always highly expressed in pollen, occurred independently in monocots and dicots. In summary, EXO70A2 is a crucial component of the exocyst complex in Arabidopsis pollen that is required for efficient plant sexual reproduction.