Identification Of miRNA Targets Research Articles

Integrative analysis in head and neck cancer reveals distinct role of miRNome and methylome as tumour epigenetic drivers

Head and neck cancer is the sixth most common malignancy worldwide, with the relatively low 5-year survival rate, mainly because it is diagnosed at a late stage. Infection with HPV is a well known aetiology, which affects the nature of these cancers and patients’ survival. Besides, it is considered that the main driving force for this type of cancer could be epigenetics. In this study we aimed to find potential epigenetic biomarkers, by integrating miRNome, methylome, and transcriptome analyses. From the fresh head and neck cancer tissue samples, we chose a group for miRNome, methylome and transcriptome profiling, in comparison to adequate control samples. Bioinformatics analyses are performed in R v4.2.2. Count normalisation and group differential expression for mRNA and the previously obtained miRNA count data was performed with DESeq2 v1.36. Gene set enrichment analysis was performed and visualised using gProfiler2 v0.2.1 Identification of miRNA targets was performed by querying in miRTarBase using multiMiR v1.18.0. Annotation of CpG sites merging into islands was obtained from RnBeads.hg19 v1.28.0. package. For the integrative analysis we performed kmeans clustering using stats v4.2.2 package, using 8–12 clusters and nstart 100. We found that transcriptome analysis divides samples into cancers and controls clusters, with no relation to HPV status or cancer anatomical location. Differentially expressed genes (n = 2781) were predominantly associated with signalling pathways of tumour progression. We identified a cluster of genes under the control of the transcription factor E2F that are significantly underexpressed in cancer tissue, as well as T cell immunity genes and genes related to regulation of transcription. Among overexpressed genes in tumours we found those that belong to cell cycle regulation and vasculature. A small number of genes were found significantly differentially expressed in HPV-positive versus HPV-negative tumours (for example NEFH, ZFR2, TAF7L, ZNF541, and TYMS). In this comprehensive study on an overlapping set of samples where the integration of miRNome, methylome and transcriptome analysis were performed for head and neck cancer, we demonstrated that the majority of genes were associated exclusively with miRNome or methylome and, to a lesser extent, under the control of both epigenetic mechanisms.

A time course analysis through diapause reveals dynamic temporal patterns of microRNAs associated with endocrine regulation in the butterfly Pieris napi.

Organisms inhabiting highly seasonal environments must cope with a wide range of environmentally induced challenges. Many seasonal challenges require extensive physiological modification to survive. In winter, to survive extreme cold and limited resources, insects commonly enter diapause, which is an endogenously derived dormant state associated with minimized cellular processes and low energetic expenditure. Due to the high degree of complexity involved in diapause, substantial cellular regulation is required, of which our understanding primarily derives from the transcriptome via messenger RNA expression dynamics. Here we aim to advance our understanding of diapause by investigating microRNA (miRNA) expression in diapausing and direct developing pupae of the butterfly Pieris napi. We identified coordinated patterns of miRNA expression throughout diapause in both head and abdomen tissues of pupae, and via miRNA target identification, found several expression patterns to be enriched for relevant diapause-related physiological processes. We also identified two candidate miRNAs, miR-14-5p and miR-2a-3p, that are likely involved in diapause progression through their activity in the ecdysone pathway, a critical regulator of diapause termination. miR-14-5p targets phantom, a gene in the ecdysone synthesis pathway, and is upregulated early in diapause. miR-2a-3p has been found to be expressed in response to ecdysone, and is upregulated during diapause termination. Together, the expression patterns of these two miRNAs match our current understanding of the timing of hormonal regulation of diapause in P. napi and provide interesting candidates to further explore the mechanistic role of microRNAs in diapause regulation.

Effects of Eribulin on the RNA Content of Extracellular Vesicles Released by Metastatic Breast Cancer Cells.

Extracellular vesicles (EVs) are small lipid particles secreted by almost all human cells into the extracellular space. They perform the essential function of cell-to-cell communication, and their role in promoting breast cancer progression has been well demonstrated. It is known that EVs released by triple-negative and highly aggressive MDA-MB-231 breast cancer cells treated with paclitaxel, a microtubule-targeting agent (MTA), promoted chemoresistance in EV-recipient cells. Here, we studied the RNA content of EVs produced by the same MDA-MB-231 breast cancer cells treated with another MTA, eribulin mesylate. In particular, we analyzed the expression of different RNA species, including mRNAs, lncRNAs, miRNAs, snoRNAs, piRNAs and tRNA fragments by RNA-seq. Then, we performed differential expression analysis, weighted gene co-expression network analysis (WGCNA), functional enrichment analysis, and miRNA-target identification. Our findings demonstrate the possible involvement of EVs from eribulin-treated cells in the spread of chemoresistance, prompting the design of strategies that selectively target tumor EVs.

MicroRNA-Target Identification: A Combinatorial In Silico Approach.

Contemporary computational target prediction tools with their distinctive properties and stringency have been playing a vital role in pursuing putative targets for a solitary miRNA or a subcategory of miRNAs. These tools utilize a defined set of probabilistic algorithms, machine learning techniques, and information of experimentally validated miRNA targets to provide the best selection. However, there are numerous false-positive predictions, and a method to choose an archetypal approach and put the data provided by the prediction tools into context is still lacking. Moreover, sensitivity, specificity, and overall efficiency of a single tool have not yet been achieved. Therefore, a systematic combination of selective online tools combining elementary and advanced factors of miRNA target identification might reinforce the current target prediction regime. The focus of this study was to build a comprehensive workflow by combining six available online tools to facilitate the current understanding of miRNA-target prediction.

A Small-Molecule Probe with a Dual Function of miRNA Inhibition and Target identification.

By virtue of their key roles in pathologies, miRNAs represent a promising class of therapeutic targets. While high-fidelity small-molecule modulators of miRNAs can be identified via high-throughput screening using cellular reporter systems, their modes of action are elusive due to the lack of proper tools. Here, we report a small-molecule probe, 1 a, that is capable of elucidating its biological target along miRNA inhibition. Derived from norathyriol, a nature product, 1 a possessed a bioorthogonal alkyne moiety for subsequent labeling via copper-catalyzed azide-alkyne cycloaddition chemistry. We demonstrated that 1 a inhibited a panel of different miRNAs by blocking their loading onto argonaute 2 (AGO2), which is the key protein responsible for miRNA function. With the alkyne handle, we successfully identified AGO2 as an intracellular target of 1 a. Therefore, this work presents a novel small-molecule tool for suppressing and probing miRNA regulatory pathways.

Identification of potential microRNAs regulating metabolic plasticity and cellular phenotypes in glioblastoma.

MicroRNAs (miRNAs) play important role in regulating cellular metabolism, and are currently being explored in cancer. As metabolic reprogramming in cancer is a major mediator of phenotypic plasticity, understanding miRNA-regulated metabolism will provide opportunities to identify miRNA targets that can regulate oncogenic phenotypes by taking control of cellular metabolism. In the present work, we studied the effect of differentially expressed miRNAs on metabolism, and associated oncogenic phenotypes in glioblastoma (GBM) using patient-derived data. Networks of differentially expressed miRNAs and metabolic genes were created and analyzed to identify important miRNAs that regulate major metabolism in GBM. Graph network-based approaches like network diffusion, backbone extraction, and different centrality measures were used to analyze these networks for identification of potential miRNA targets. Important metabolic processes and cellular phenotypes were annotated to trace the functional responses associated with these miRNA-regulated metabolic genes and associated phenotype networks. miRNA-regulated metabolic gene subnetworks of cellular phenotypes were extracted, and important miRNAs regulating these phenotypes were identified. The most important outcome of the study is the target miRNA combinations predicted for five different oncogenic phenotypes that can be tested experimentally for miRNA-based therapeutic design in GBM. Strategies implemented in the study can be used to generate testable hypotheses in other cancer types as well, and design context-specific miRNA-based therapy for individual patient. Their usability can be further extended to other gene regulatory networks in cancer and other genetic diseases.

Parallel analysis of RNA ends reveals global microRNA-mediated target RNA cleavage in maize.

MicroRNAs (miRNAs) are endogenous 20-24-nucleotide non-coding RNAs that play important regulatory roles in many biological processes in eukaryotes. miRNAs modulate the expression of target genes at the post-transcriptional level by transcript cleavage or translational inhibition. The identification of miRNA target genes has been extensively investigated in Arabidopsis and rice, but an in-depth global analysis of miRNA-mediated target regulation is still lacking in maize. Here, we report a transcriptome-wide identification of miRNA targets by analyzing parallel analysis of RNA ends (PARE) datasets derived from nine different tissues at five developmental stages of the maize (Zea mays L.) B73 cultivar. In total, 246 targets corresponding to 60 miRNAs from 25 families were identified, including transcription factors and other genes. In addition, PARE analysis revealed that miRNAs guide specific target transcript cleavage in a tissue-preferential manner. Primary transcripts of MIR159c and MIR169e were found to be cleaved by mature miR159 and miR169, respectively, indicating a negative-feedback regulatory mechanism in miRNA biogenesis. Moreover, several miRNA-target gene pairs involved in seed germination were identified and experimentally validated. Our PARE analyses generated a wide and detailed miRNA-target interaction atlas, which provides a valuable resource for investigating the roles of miRNAs and their targets in maize.

Multi-Relation Graph Embedding for Predicting miRNA-Target Gene Interactions by Integrating Gene Sequence Information.

Accumulated studies have found that miRNAs are in charge of many complex diseases such as cancers by modulating gene expression. Predicting miRNA-target interactions is beneficial for uncovering the crucial roles of miRNAs in regulating target genes and the progression of diseases. The emergence of large-scale genomic and biological data as well as the recent development in heterogeneous networks provides new opportunities for miRNA target identification. Compared with conventional methods, computational methods become a decent solution for high efficiency. Thus, designing a method that could excavate valid information from the heterogeneous network and gene sequences is in great demand for improving the prediction accuracy. In this study, we proposed a graph-based model named MRMTI for the prediction of miRNA-target interactions. MRMTI utilized the multi-relation graph convolution module and the Bi-LSTM module to incorporate both network topology and sequential information. The learned embeddings of miRNAs and genes were then used to calculate the prediction scores of miRNA-target pairs. Comparisons with other state-of-the-art graph embedding methods and existing bioinformatic tools illustrated the superiority of MRMTI under multiple criteria metrics. Three variants of MRMTI implied the positive effect of multi-relation. The experimental results of case studies further demonstrated the prominent ability of MRMTI in predicting novel associations.

Recent Development of Bioinformatics Tools for microRNA Target Prediction.

MicroRNAs (miRNAs) are central players that regulate the post-transcriptional processes of gene expression. Binding of miRNAs to target mRNAs can repress their translation by inducing the degradation or by inhibiting the translation of the target mRNAs. Highthroughput experimental approaches for miRNA target identification are costly and timeconsuming, depending on various factors. It is vitally important to develop bioinformatics methods for accurately predicting miRNA targets. With the increase of RNA sequences in the post-genomic era, bioinformatics methods are being developed for miRNA studies especially for miRNA target prediction. This review summarizes the current development of state-of-the-art bioinformatics tools for miRNA target prediction, points out the progress and limitations of the available miRNA databases, and their working principles. Finally, we discuss the caveat and perspectives of the next-generation algorithms for the prediction of miRNA targets.

Experimental MicroRNA Targeting Validation.

microRNAs (miRNAs) have recently been recognized as a new dimension of posttranscriptional regulation. It is well defined that most human protein-coding genes are regulated by one or more miRNAs. Therefore, it is crucial to identify genes targeted by the miRNAs to better understand their functions. Although bioinformatics tools have the ability to identify target candidates it is still essential to identify physiological targets by experimental approaches. Currently, the majority of miRNA-target experimental validation approaches assess the changes in target expression in mRNA or protein level upon miRNA upregulation or downregulation. Additionally, finding out direct physical interactions between miRNAs and their targets is also among the experimental techniques. In this chapter we reviewed the existing experimental techniques for miRNA target identification by considering their advantages and potential drawbacks.

LncRNA MIR503HG inhibits cell proliferation and promotes apoptosis in TNBC cells via the miR-224-5p/HOXA9 axis

Triple-negative breast cancer (TNBC) is a highly invasive subtype of breast cancer. This study investigated the molecular mechanism and influences of MIR503HG, miR-224-5p, and homeobox A9 (HOXA9) on TNBC cell growth and migration. Dual-luciferase reporter gene and RNA immunoprecipitation were performed to examine the regulation of MIR503HG, miR-224-5p, and HOXA9. Cell proliferation, apoptosis, migration, and invasion were evaluated by colony formation, flow cytometry, and Transwell assays. Finally, nude mice were employed to investigate the influence of MIR503HG on TNBC tumor growth. HOXA9 protein levels were detected by immunohistochemical staining. MIR503HG and HOXA9 expression were reduced in TNBC, while miR-224-5p was increased. Overexpression of MIR503HG or HOXA9 reduced the cell migration ability and proliferation and promoted apoptosis, and knockdown of MIR503HG or overexpression of miR-224-5p exhibited the opposite effects. Furthermore, MIR503HG promoted HOXA9 expression by inhibiting miR-224-5p. Overexpression of miR-224-5p reversed the effects of MIR503HG overexpression on TNBC cells, while overexpression of HOXA9 reversed the effect of MIR503HG knockdown. Additionally, an in vivo study proved that MIR503HG inhibited TNBC tumor growth via the miR-224-5p/HOXA9 axis. MIR503HG inhibited cell proliferation and promoted the apoptosis of TNBC cells via the miR-224-5p/HOXA9 axis, which may function as a novel target for the treatment of TNBC.

Identification of miRNA targets in eggplant in response to Verticillium dahliae by degradome sequencing

Verticillium wilt is a vascular disease caused by Verticillium dahliae, which has a serious impact on the yield and quality of eggplant. MiRNAs regulates plant growth, development, environmental adaptation and other life activities by controlling the expression of target genes. Although miRNAs have been systematically studied by high-throughput sequencing in eggplant (Solanum melongena L.), their target genes are not identified systematically, which would provide the basis for exploring the mechanism of miRNA mediated gene regulation in response to Verticillium wilt of eggplant. In this study, degradome sequencing was performed using two libraries separately prepared from mock-inoculated and V. dahliae-inoculated seedlings of eggplants. A total of 122 target genes for 49 miRNAs families were identified. Of them, 62 target genes were significantly induced by V. dahliae, including 34 targets were found only in the inoculated seedlings library and 28 targets were shown to be differentially expressed between both two libraries. Further analysis showed that a conserved miRNA could target various genes ranging from one up to 15 or a target gene could be cleaved by 1–5 different miRNAs. QRT-PCR analysis on five miRNAs and their target genes confirmed the reliability of the degradome sequencing data. GO analysis revealed that target genes owned diverse biological functions and transcription regulation was the largest functional category. Analysis on KEGG showed that target genes were mainly involved in plant-pathogen interaction pathway and plant hormone signal transduction pathway to resist disease. This result will provide basic information for further studying the regulatory mechanism of eggplant miRNAs in response to Verticillium wilt infection.

A multilevel analysis of hiv1-miR-H1 miRNA using KPCA, K-means, Random Forest and online target tools

The goal of this study was to propose a workflow using machine learning to identify and predict the miRNA targets of Human Immunodeficiency virus 1. miRNAs which is ~21 nt long are attained from larger hairpin RNA precursors and is maintained in the secondary structure of their precursor relatively than in primary chain of successions. The proposition approach for identification and prediction of miRNA targets in hiv1-miR-H1is based on secondary structure and E-value through machine learning. Data Linearity of Length and e-value for sequence match with hiv1-mir-H1 is verified using Kernel PCA. miRNA targets were grouped into clusters thereby indicating similar targets using K-means algorithm. Classification model using Random Forest was implemented regards to each secondary features variable considering feature relevance. A learning methodology is put forward that assimilate and integrate the score returned by various machine learning algorithms to predict cellular hiv1-miR-H1 targets. Gene targets results using TargetScan, miRanda, PITA, DIANA microT and RNAhybrid are also explored for multiple parameters.

MiRNA Targets: From Prediction Tools to Experimental Validation.

MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression in both animals and plants. By pairing to microRNA responsive elements (mREs) on target mRNAs, miRNAs play gene-regulatory roles, producing remarkable changes in several physiological and pathological processes. Thus, the identification of miRNA-mRNA target interactions is fundamental for discovering the regulatory network governed by miRNAs. The best way to achieve this goal is usually by computational prediction followed by experimental validation of these miRNA-mRNA interactions. This review summarizes the key strategies for miRNA target identification. Several tools for computational analysis exist, each with different approaches to predict miRNA targets, and their number is constantly increasing. The major algorithms available for this aim, including Machine Learning methods, are discussed, to provide practical tips for familiarizing with their assumptions and understanding how to interpret the results. Then, all the experimental procedures for verifying the authenticity of the identified miRNA-mRNA target pairs are described, including High-Throughput technologies, in order to find the best approach for miRNA validation. For each strategy, strengths and weaknesses are discussed, to enable users to evaluate and select the right approach for their interests.

Identification of primary copy number variations reveal enrichment of Calcium, and MAPK pathways sensitizing secondary sites for autism

BackgroundAutism is a neurodevelopmental condition with genetic heterogeneity. It is characterized by difficulties in reciprocal social interactions with strong repetitive behaviors and stereotyped interests. Copy number variations (CNVs) are genomic structural variations altering the genomic structure either by duplication or deletion. De novo or inherited CNVs are found in 5–10% of autistic subjects with a size range of few kilobases to several megabases. CNVs predispose humans to various diseases by altering gene regulation, generation of chimeric genes, and disruption of the coding region or through position effect. Although, CNVs are not the initiating event in pathogenesis; additional preceding mutations might be essential for disease manifestation. The present study is aimed to identify the primary CNVs responsible for autism susceptibility in healthy cohorts to sensitize secondary-hits. In the current investigation, primary-hit autism gene CNVs are characterized in 1715 healthy cohorts of varying ethnicities across 12 populations using Affymetrix high-resolution array study. Thirty-eight individuals from twelve families residing in Karnataka, India, with the age group of 13–73 years are included for the comparative CNV analysis. The findings are validated against global 179 autism whole-exome sequence datasets derived from Simons Simplex Collection. These datasets are deposited at the Simons Foundation Autism Research Initiative (SFARI) database.ResultsThe study revealed that 34.8% of the subjects carried 2% primary-hit CNV burden with 73 singleton-autism genes in different clusters. Of these, three conserved CNV breakpoints were identified with ARHGAP11B, DUSP22, and CHRNA7 as the target genes across 12 populations. Enrichment analysis of the population-specific autism genes revealed two signaling pathways—calcium and mitogen-activated protein kinases (MAPK) in the CNV identified regions. These impaired pathways affected the downstream cascades of neuronal function and physiology, leading to autism behavior. The pathway analysis of enriched genes unravelled complex protein interaction networks, which sensitized secondary sites for autism. Further, the identification of miRNA targets associated with autism gene CNVs added severity to the condition.ConclusionThese findings contribute to an atlas of primary-hit genes to detect autism susceptibility in healthy cohorts, indicating their impact on secondary sites for manifestation.

Therapeutic potential of miRNAs targeting SARS-CoV-2 host cell receptor ACE2

In late December 2019, several cases of pneumonia of unknown etiology (COVID-19) were reported in Wuhan, Hubei province, China. Based on clinical findings, blood tests and chest radiographs, this disease was diagnosed as a virus-associated pneumonia. Sequence analysis revealed a novel coronavirus, called SARS-CoV-2 (formerly called 2019-nCoV), as the causative agent of pneumonia of unknown etiology. So far, the SARS-CoV-2 infection continues to spread, and this virus poses a serious public health threat. In this study, it was aimed to reveal potential miRNA targets for the regulation of SARS-CoV-2 host cell receptor ACE2. For the identification of potential miRNA targets for the ACE2 gene, TarBase v.8 (DIANA Tools), TargetScan, miRTarBase and miRDB miRNA-target prediction algorithms were used. FANTOM5 CAGE was used for the cellular ontology analysis. Expression levels of these miRNAs were determined using OncomiR Pan-Cancer miRNome Atlas. The results suggest that members of miR-200 family of miRNAs, especially miR-200c-3p, are strong candidate targets for the regulation of ACE2 in respiratory system cells. Consequently, the present study for the first time emphasizes potential use of miRNA-based therapeutics in the battle against SARS-CoV-2 infection and its deadly disease, COVID-19.

Functional Analyses of Bovine Foamy Virus-Encoded miRNAs Reveal the Importance of a Defined miRNA for Virus Replication and Host-Virus Interaction.

In addition to regulatory or accessory proteins, some complex retroviruses gain a repertoire of micro-RNAs (miRNAs) to regulate and control virus–host interactions for efficient replication and spread. In particular, bovine and simian foamy viruses (BFV and SFV) have recently been shown to express a diverse set of RNA polymerase III-directed miRNAs, some with a unique primary miRNA double-hairpin, dumbbell-shaped structure not known in other viruses or organisms. While the mechanisms of expression and structural requirements have been studied, the functional importance of these miRNAs is still far from understood. Here, we describe the in silico identification of BFV miRNA targets and the subsequent experimental validation of bovine Ankyrin Repeat Domain 17 (ANKRD17) and Bax-interacting factor 1 (Bif1) target genes in vitro and, finally, the suppression of ANKRD17 downstream genes in the affected pathway. Deletion of the entire miRNA cassette in the non-coding part of the U3 region of the long terminal repeats attenuated replication of corresponding BFV mutants in bovine cells. This repression can be almost completely trans-complemented by the most abundant miRNA BF2-5p having the best scores for predicted and validated BFV miRNA target genes. Deletion of the miRNA cassette does not grossly affect particle release and overall particle composition.

Synthetic circular miR-21 RNA decoys enhance tumor suppressor expression and impair tumor growth in mice.

Naturally occurring circular RNAs efficiently impair miRNA functions. Synthetic circular RNAs may thus serve as potent agents for miRNA inhibition. Their therapeutic effect critically relies on (i) the identification of optimal miRNA targets, (ii) the optimization of decoy structures and (iii) the development of efficient formulations for their use as drugs. In this study, we extensively explored the functional relevance of miR-21-5p in cancer cells. Analyses of cancer transcriptomes reveal that miR-21-5p is the by far most abundant miRNA in human cancers. Deletion of the MIR21 locus in cancer-derived cells identifies several direct and indirect miR-21-5p targets, including major tumor suppressors with prognostic value across cancers. To impair miR-21-5p activities, we evaluate synthetic, circular RNA decoys containing four repetitive binding elements. In cancer cells, these decoys efficiently elevate tumor suppressor expression and impair tumor cell vitality. For their in vivo delivery, we for the first time evaluate the formulation of decoys in polyethylenimine (PEI)-based nanoparticles. We demonstrate that PEI/decoy nanoparticles lead to a significant inhibition of tumor growth in a lung adenocarcinoma xenograft mouse model via the upregulation of tumor suppressor expression. These findings introduce nanoparticle-delivered circular miRNA decoys as a powerful potential therapeutic strategy in cancer treatment.

MicroRNAs and Their Targetomes in Tumor-Immune Communication.

The development of cancer is a complex and dynamically regulated multiple-step process that involves many changes in gene expression. Over the last decade, microRNAs (miRNAs), a class of short regulatory non-coding RNAs, have emerged as key molecular effectors and regulators of tumorigenesis. While aberrant expression of miRNAs or dysregulated miRNA-mediated gene regulation in tumor cells have been shown to be capable of directly promoting or inhibiting tumorigenesis, considering the well-reported role of the immune system in cancer, tumor-derived miRNAs could also impact tumor growth through regulating anti-tumor immune responses. Here, we discuss howmiRNAs can function as central mediators that influence the crosstalk between cancer and the immune system. Moreover, we also review the current progress in the development of novel experimental approaches for miRNA target identification that will facilitate our understanding of miRNA-mediated gene regulation in not only human malignancies, but also in other genetic disorders.

High-Resolution In Vivo Identification of miRNA Targets by Halo-Enhanced Ago2 Pull-Down

The identification of microRNA (miRNA) targets by Ago2 crosslinking-immunoprecipitation (CLIP) methods has provided major insights into the biology of this important class of non-coding RNAs. However, these methods are technically challenging and not easily applicable to an invivo setting. To overcome these limitations and facilitate the investigation of miRNA functions invivo, we have developed a method based on a genetically engineered mouse harboring a conditional Halo-Ago2 allele expressed from the endogenous Ago2 locus. By using a resin conjugated to the HaloTag ligand, Ago2-miRNA-mRNA complexes can be purified from cells and tissues expressing the endogenous Halo-Ago2 allele. We demonstrate the reproducibility and sensitivity of this method in mouse embryonic stem cells, developing embryos, adult tissues, and autochthonous mouse models of human brain and lung cancers. This method and the datasets we have generated will facilitate the characterization of miRNA-mRNA networks invivo under physiological and pathological conditions.