Minimum information about a microarray experiment (MIAME)-toward standards for microarray data

DDBJ update: the Genomic Expression Archive (GEA) for functional genomics data

The Genomic Expression Archive (GEA) for functional genomics data from microarray and high-throughput sequencing experiments has been established at the DNA Data Bank of Japan (DDBJ) Center (https://www.ddbj.nig.ac.jp), which is a member of the International Nucleotide Sequence Database Collaboration (INSDC) with the US National Center for Biotechnology Information and the European Bioinformatics Institute. The DDBJ Center collects nucleotide sequence data and associated biological information from researchers and also services the Japanese Genotype–phenotype Archive (JGA) with the National Bioscience Database Center for collecting human data. To automate the submission process, we have implemented the DDBJ BioSample validator which checks submitted records, auto-corrects their format, and issues error messages and warnings if necessary. The DDBJ Center also operates the NIG supercomputer, prepared for analyzing large-scale genome sequences. We now offer a secure platform specifically to handle personal human genomes. This report describes database activities for INSDC and JGA over the past year, the newly launched GEA, submission, retrieval, and analysis services available in our supercomputer system and their recent developments.

Community standards for open cell migration data

Cell migration research has become a high-content field. However, the quantitative information encapsulated in these complex and high-dimensional datasets is not fully exploited owing to the diversity of experimental protocols and non-standardized output formats. In addition, typically the datasets are not open for reuse. Making the data open and Findable, Accessible, Interoperable, and Reusable (FAIR) will enable meta-analysis, data integration, and data mining. Standardized data formats and controlled vocabularies are essential for building a suitable infrastructure for that purpose but are not available in the cell migration domain. We here present standardization efforts by the Cell Migration Standardisation Organisation (CMSO), an open community-driven organization to facilitate the development of standards for cell migration data. This work will foster the development of improved algorithms and tools and enable secondary analysis of public datasets, ultimately unlocking new knowledge of the complex biological process of cell migration.

The Consequences of a Disruption in Cyto-Nuclear Coadaptation on the Molecular Response to a Nitrate Starvation in Arabidopsis

Mitochondria and chloroplasts are important actors in the plant nutritional efficiency. So, it could be expected that a disruption of the coadaptation between nuclear and organellar genomes impact plant response to nutrient stresses. We addressed this issue using two Arabidopsis accessions, namely Ct1 and Jea, and their reciprocal cytolines possessing the nuclear genome from one parent and the organellar genomes of the other one. We measured gene expression, and quantified proteins and metabolites under N starvation and non-limiting conditions. We observed a typical response to N starvation at the phenotype and molecular levels. The phenotypical response to N starvation was similar in the cytolines compared to the parents. However, we observed an effect of the disruption of genomic coadaptation at the molecular levels, distinct from the previously described responses to organellar stresses. Strikingly, genes differentially expressed in cytolines compared to parents were mainly repressed in the cytolines. These genes encoded more mitochondrial and nuclear proteins than randomly expected, while N starvation responsive ones were enriched in genes for chloroplast and nuclear proteins. In cytolines, the non-coadapted cytonuclear genomic combination tends to modulate the response to N starvation observed in the parental lines on various biological processes.

Urinary microRNAs expression in prostate cancer diagnosis: a systematic review

PURPOSE

Circulating microRNAs (miRNAs) have been shown to have the potential as noninvasive diagnosis biomarkers in several types of cancers, including prostate cancer (PCa). Urine-based miRNA biomarkers have been researched as an alternative tool in PCa diagnosis. However, few studies have performed miRNA detection in urine samples from PCa patients, as well as low numbers of miRNAs have been assayed, and there is a lack of standard strategies for validation. In this context, we conducted an in-depth literature review focusing on miRNAs isolated from urine samples that may contribute to the diagnosis of PCa.

METHODS

A systematic review was performed searching the PubMed, Lilacs and Cochrane Library databases for articles focused on the value of significantly deregulated miRNAs as biomarkers in PCa patients.

RESULTS

Only 18 primary manuscripts were included in this review, according to the search criteria. Our results suggest that miR-21-5p, miR-141-3p, miR-375 and miR-574-3p should be considered as potential urinary biomarkers for the diagnosis of PCa.

CONCLUSION

These results suggested that large-scale prospective studies are still needed to validate our findings, using standardized protocols for analysis.

Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects

The starting point of successful hazard assessment is the generation of unbiased and trustworthy data. Conventional toxicity testing deals with extensive observations of phenotypic endpoints in vivo and complementing in vitro models. The increasing development of novel materials and chemical compounds dictates the need for a better understanding of the molecular changes occurring in exposed biological systems. Transcriptomics enables the exploration of organisms' responses to environmental, chemical, and physical agents by observing the molecular alterations in more detail. Toxicogenomics integrates classical toxicology with omics assays, thus allowing the characterization of the mechanism of action (MOA) of chemical compounds, novel small molecules, and engineered nanomaterials (ENMs). Lack of standardization in data generation and analysis currently hampers the full exploitation of toxicogenomics-based evidence in risk assessment. To fill this gap, TGx methods need to take into account appropriate experimental design and possible pitfalls in the transcriptomic analyses as well as data generation and sharing that adhere to the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. In this review, we summarize the recent advancements in the design and analysis of DNA microarray, RNA sequencing (RNA-Seq), and single-cell RNA-Seq (scRNA-Seq) data. We provide guidelines on exposure time, dose and complex endpoint selection, sample quality considerations and sample randomization. Furthermore, we summarize publicly available data resources and highlight applications of TGx data to understand and predict chemical toxicity potential. Additionally, we discuss the efforts to implement TGx into regulatory decision making to promote alternative methods for risk assessment and to support the 3R (reduction, refinement, and replacement) concept. This review is the first part of a three-article series on Transcriptomics in Toxicogenomics. These initial considerations on Experimental Design, Technologies, Publicly Available Data, Regulatory Aspects, are the starting point for further rigorous and reliable data preprocessing and modeling, described in the second and third part of the review series.

Transcriptomic Profiling in Fins of Atlantic Salmon Parasitized with Sea Lice: Evidence for an Early Imbalance Between Chalimus-Induced Immunomodulation and the Host's Defense Response

Parasitic sea lice (e.g., Lepeophtheirus salmonis) cause costly outbreaks in salmon farming. Molecular insights into parasite-induced host responses will provide the basis for improved management strategies. We investigated the early transcriptomic responses in pelvic fins of Atlantic salmon parasitized with chalimus I stage sea lice. Fin samples collected from non-infected (i.e. pre-infected) control (PRE) and at chalimus-attachment sites (ATT) and adjacent to chalimus-attachment sites (ADJ) from infected fish were used in profiling global gene expression using 44 K microarrays. We identified 6568 differentially expressed probes (DEPs, FDR < 5%) that included 1928 shared DEPs between ATT and ADJ compared to PRE. The ATT versus ADJ comparison revealed 90 DEPs, all of which were upregulated in ATT samples. Gene ontology/pathway term network analyses revealed profound changes in physiological processes, including extracellular matrix (ECM) degradation, tissue repair/remodeling and wound healing, immunity and defense, chemotaxis and signaling, antiviral response, and redox homeostasis in infected fins. The QPCR analysis of 37 microarray-identified transcripts representing these functional themes served to confirm the microarray results with a significant positive correlation (p < 0.0001). Most immune/defense-relevant transcripts were downregulated in both ATT and ADJ sites compared to PRE, suggesting that chalimus exerts immunosuppressive effects in the salmon's fins. The comparison between ATT and ADJ sites demonstrated the upregulation of a suite of immune-relevant transcripts, evidencing the salmon's attempt to mount an anti-lice response. We hypothesize that an imbalance between immunomodulation caused by chalimus during the early phase of infection and weak defense response manifested by Atlantic salmon makes it a susceptible host for L. salmonis.

MicroRNAs associated to single drug components of R-CHOP identifies diffuse large B-cell lymphoma patients with poor outcome and adds prognostic value to the international prognostic index

Background

Treatment resistance is a major clinical challenge of diffuse large B-cell lymphoma (DLBCL) where approximately 40% of the patients have refractory disease or relapse. Since DLBCL is characterized by great clinical and molecular heterogeneity, the purpose of the present study was to investigate whether miRNAs associated to single drug components of R-CHOP can improve robustness of individual markers and serve as a prognostic classifier.

Methods

Fifteen DLBCL cell lines were tested for sensitivity towards single drug compounds of the standard treatment R-CHOP: rituximab (R), cyclophosphamide (C), doxorubicin (H), and vincristine (O). For each drug, cell lines were ranked using the area under the dose-response curve and grouped as either sensitive, intermediate or resistant. Baseline miRNA expression data were obtained for each cell line in untreated condition, and differential miRNA expression analysis between sensitive and resistant cell lines identified 43 miRNAs associated to growth response after exposure towards single drugs of R-CHOP. Using the Affymetrix HG-U133 platform, expression levels of miRNA precursors were assessed in 701 diagnostic DLBCL biopsies, and miRNA-panel classifiers predicting disease progression were build using multiple Cox regression or random survival forest. Classifiers were validated and ranked by repeated cross-validation.

Results

Prognostic accuracies were assessed by Brier Scores and time-varying area under the ROC curves, which revealed better performance of multivariate Cox models compared to random survival forest models. The Cox model including miR-146a, miR-155, miR-21, miR-34a, and miR-23a~miR-27a~miR-24-2 cluster performed the best and successfully stratified GCB-DLBCL patients into high- and low-risk of disease progression. In addition, combination of the Cox miRNA-panel and IPI substantially increased prognostic performance in GCB classified patients.

Conclusion

As a proof of concept, we found that expression data of drug associated miRNAs display prognostic utility and adding these to IPI improves prognostic stratification of GCB-DLBCL patients treated with R-CHOP.

Minimum Information and Quality Standards for Conducting, Reporting, and Organizing In Vitro Research

Insufficient description of experimental practices can contribute to difficulties in reproducing research findings. In response to this, "minimum information" guidelines have been developed for different disciplines. These standards help ensure that the complete experiment is described, including both experimental protocols and data processing methods, allowing a critical evaluation of the whole process and the potential recreation of the work. Selected examples of minimum information checklists with relevance for in vitro research are presented here and are collected by and registered at the MIBBI/FAIRsharing Information Resource portal.In addition, to support integrative research and to allow for comparisons and data sharing across studies, ontologies and vocabularies need to be defined and integrated across areas of in vitro research. As examples, this chapter addresses ontologies for cells and bioassays and discusses their importance for in vitro studies.Finally, specific quality requirements for important in vitro research tools (like chemical probes, antibodies, and cell lines) are suggested, and remaining issues are discussed.

Profiling the transcriptome response of Atlantic salmon head kidney to formalin-killed Renibacterium salmoninarum

Renibacterium salmoninarum is a Gram-positive, intracellular bacterial pathogen that causes Bacterial Kidney Disease (BKD) in Atlantic salmon (Salmo salar). The host transcriptomic response to this immune-suppressive pathogen remains poorly understood. To identify R. salmoninarum-responsive genes, Atlantic salmon were intraperitoneally injected with a low (5 × 10⁵ cells/kg, Low-Rs) or high (5 × 10⁷ cells/kg; High-Rs) dose of formalin-killed R. salmoninarum bacterin or phosphate-buffered saline (PBS control); head kidney samples were collected before and 24 h after injection. Using 44K microarray analysis, we identified 107 and 345 differentially expressed probes in response to R. salmoninarum bacterin (i.e. High-Rs vs. PBS control) by Significance Analysis of Microarrays (SAM) and Rank Products (RP), respectively. Twenty-two microarray-identified genes were subjected to qPCR assays, and 17 genes were confirmed as being significantly responsive to the bacterin. There was an up-regulation in expression of genes playing putative roles as immune receptors and antimicrobial effectors. Genes with putative roles as pathogen recognition (e.g. clec12b and tlr5) or immunoregulatory (e.g. tnfrsf6b and tnfrsf11b) receptors were up-regulated in response to R.salmoninarum bacterin. Also, chemokines and a chemokine receptor showed opposite regulation [up-regulation of effectors (i.e. ccl13 and ccl) and down-regulation of cxcr1] in response to the bacterin. The present study identified and validated novel biomarker genes (e.g. ctsl1, lipe, cldn4, ccny) that can be used to assess Atlantic salmon response to R. salmoninarum, and will be valuable in the development of tools to combat BKD.

Ten simple rules for providing effective bioinformatics research support

Life scientists are increasingly turning to high-throughput sequencing technologies in their research programs, owing to the enormous potential of these methods. In a parallel manner, the number of core facilities that provide bioinformatics support are also increasing. Notably, the generation of complex large datasets has necessitated the development of bioinformatics support core facilities that aid laboratory scientists with cost-effective and efficient data management, analysis, and interpretation. In this article, we address the challenges-related to communication, good laboratory practice, and data handling-that may be encountered in core support facilities when providing bioinformatics support, drawing on our own experiences working as support bioinformaticians on multidisciplinary research projects. Most importantly, the article proposes a list of guidelines that outline how these challenges can be preemptively avoided and effectively managed to increase the value of outputs to the end user, covering the entire research project lifecycle, including experimental design, data analysis, and management (i.e., sharing and storage). In addition, we highlight the importance of clear and transparent communication, comprehensive preparation, appropriate handling of samples and data using monitoring systems, and the employment of appropriate tools and standard operating procedures to provide effective bioinformatics support.

Data libraries - the missing element for modeling biological systems

The primary bottleneck in understanding and modeling biological systems is shifting from data collection to data analysis and integration. This process critically depends on data being available in an organized form, so that they can be accessed, understood, and reused by a broad community of scientists. A proven solution for organizing data is literature curation, which extracts, aggregates, and distributes findings from publications. Here, I describe the benefits of extending curation practices to datasets, especially those that are not deposited in centralized databases. I argue that dataset curation (or ‘data librarianship’ as I suggest we call it) will overcome many barriers in data visibility and reusability and make a unique contribution to integration and modeling.

Whole embryo culture, transcriptomics and RNA interference identify TBX1 and FGF11 as novel regulators of limb development in the mouse

Identifying genes involved in vertebrate developmental processes and characterizing this involvement are daunting tasks, especially in the mouse where viviparity complicates investigations. Attempting to devise a streamlined approach for this type of study we focused on limb development. We cultured E10.5 and E12.5 embryos and performed transcriptional profiling to track molecular changes in the forelimb bud over a 6-hour time-window. The expression of certain genes was found to diverge rapidly from its normal path, possibly reflecting the activation of a stress-induced response. Others, however, maintained for up to 3 hours dynamic expression profiles similar to those seen in utero. Some of these resilient genes were known regulators of limb development. The implication of the others in this process was either unsuspected or unsubstantiated. The localized knockdown of two such genes, Fgf11 and Tbx1, hampered forelimb bud development, providing evidence of their implication. These results show that combining embryo culture, transcriptome analysis and RNA interference could speed up the identification of genes involved in a variety of developmental processes, and the validation of their implication.

Evaluating visual analytics for health informatics applications: a systematic review from the American Medical Informatics Association Visual Analytics Working Group Task Force on Evaluation

OBJECTIVE

This article reports results from a systematic literature review related to the evaluation of data visualizations and visual analytics technologies within the health informatics domain. The review aims to (1) characterize the variety of evaluation methods used within the health informatics community and (2) identify best practices.

METHODS

A systematic literature review was conducted following PRISMA guidelines. PubMed searches were conducted in February 2017 using search terms representing key concepts of interest: health care settings, visualization, and evaluation. References were also screened for eligibility. Data were extracted from included studies and analyzed using a PICOS framework: Participants, Interventions, Comparators, Outcomes, and Study Design.

RESULTS

After screening, 76 publications met the review criteria. Publications varied across all PICOS dimensions. The most common audience was healthcare providers (n = 43), and the most common data gathering methods were direct observation (n = 30) and surveys (n = 27). About half of the publications focused on static, concentrated views of data with visuals (n = 36). Evaluations were heterogeneous regarding setting and measurements used.

DISCUSSION

When evaluating data visualizations and visual analytics technologies, a variety of approaches have been used. Usability measures were used most often in early (prototype) implementations, whereas clinical outcomes were most common in evaluations of operationally-deployed systems. These findings suggest opportunities for both (1) expanding evaluation practices, and (2) innovation with respect to evaluation methods for data visualizations and visual analytics technologies across health settings.

CONCLUSION

Evaluation approaches are varied. New studies should adopt commonly reported metrics, context-appropriate study designs, and phased evaluation strategies.

Non-Viral in Vitro Gene Delivery: It is Now Time to Set the Bar!

Transfection by means of non-viral gene delivery vectors is the cornerstone of modern gene delivery. Despite the resources poured into the development of ever more effective transfectants, improvement is still slow and limited. Of note, the performance of any gene delivery vector in vitro is strictly dependent on several experimental conditions specific to each laboratory. The lack of standard tests has thus largely contributed to the flood of inconsistent data underpinning the reproducibility crisis. A way researchers seek to address this issue is by gauging the effectiveness of newly synthesized gene delivery vectors with respect to benchmarks of seemingly well-known behavior. However, the performance of such reference molecules is also affected by the testing conditions. This survey points to non-standardized transfection settings and limited information on variables deemed relevant in this context as the major cause of such misalignments. This review provides a catalog of conditions optimized for the gold standard and internal reference, 25 kDa polyethyleneimine, that can be profitably replicated across studies for the sake of comparison. Overall, we wish to pave the way for the implementation of standardized protocols in order to make the evaluation of the effectiveness of transfectants as unbiased as possible.

Molecular Basis of Growth Inhibition by Acetate of an Adenylate Cyclase-Deficient Mutant of Corynebacterium glutamicum

In Corynebacterium glutamicum, cyclic adenosine monophosphate (cAMP) serves as an effector of the global transcriptional regulator GlxR. Synthesis of cAMP is catalyzed by the membrane-bound adenylate cyclase CyaB. In this study, we investigated the consequences of decreased intracellular cAMP levels in a ΔcyaB mutant. While no growth defect of the ΔcyaB strain was observed on glucose, fructose, sucrose, or gluconate alone, the addition of acetate to these growth media resulted in a severe growth inhibition, which could be reversed by plasmid-based cyaB expression or by supplementation of the medium with cAMP. The effect was concentration- and pH-dependent, suggesting a link to the uncoupling activity of acetate. In agreement, the ΔcyaB mutant had an increased sensitivity to the protonophore carbonyl cyanide m-chlorophenyl hydrazone (CCCP). The increased uncoupler sensitivity correlated with a lowered membrane potential of acetate-grown ΔcyaB cells compared to wild-type cells. A reduced membrane potential affects major cellular processes, such as ATP synthesis by F1F O -ATP synthase and numerous transport processes. The impaired membrane potential of the ΔcyaB mutant could be due to a decreased expression of the cytochrome bc 1-aa 3 supercomplex, which is the major contributor of proton-motive force in C. glutamicum. Expression of the supercomplex genes was previously reported to be activated by GlxR-cAMP. A suppressor mutant of the ΔcyaB strain with improved growth on acetate was isolated, which carried a single mutation in the genome leading to an Ala131Thr exchange in GlxR. Introduction of this point mutation into the original ΔcyaB mutant restored the growth defect on acetate. This supported the importance of GlxR for the phenotype of the ΔcyaB mutant and, more generally, of the cAMP-GlxR system for the control of energy metabolism in C. glutamicum.

Guidelines for systematic reporting of sequence alignments

Bioinformatics methods are increasingly needed and used to analyze and interpret extensive datasets many of which are produced by diverse high-throughput technologies. Unfortunately, it is quite common that published articles do not contain sufficient information to allow the reader to fully comprehend and repeat computational and other studies. Guidelines were developed for reporting studies and results from sequence alignment. Brief and concise checklist of required data items was compiled making it easy to provide necessary details. Implementation of the guidelines requires similar meticulous attitude toward details as other parts of publications. If the journal does not allow reporting full details in the main article, it can be provided in supplementary material. It is important to make the alignments available. Systematic and detailed description of bioinformatics analyses adds to the value of papers and makes it easier for the scientific community to evaluate, understand, verify, and extend the published articles and their results.

All of gene expression (AOE): An integrated index for public gene expression databases

Gene expression data have been archived as microarray and RNA-seq datasets in two public databases, Gene Expression Omnibus (GEO) and ArrayExpress (AE). In 2018, the DNA DataBank of Japan started a similar repository called the Genomic Expression Archive (GEA). These databases are useful resources for the functional interpretation of genes, but have been separately maintained and may lack RNA-seq data, while the original sequence data are available in the Sequence Read Archive (SRA). We constructed an index for those gene expression data repositories, called All Of gene Expression (AOE), to integrate publicly available gene expression data. The web interface of AOE can graphically query data in addition to the application programming interface. By collecting gene expression data from RNA-seq in the SRA, AOE also includes data not included in GEO and AE. AOE is accessible as a search tool from the GEA website and is freely available at https://aoe.dbcls.jp/.

Protocol for DNA Microarrays on Glass Slides

The DNA microarray is a powerful, flexible, nonbiased discovery technology. Microarrays can be used to assess processes from gene expression to long noncoding RNAs to specific pathologies, as well as many others. This chapter describes the protocol for DNA microarray analysis of differential gene expression using DNA sequences spotted on microscope slides.

Comparative analysis of lung and blood transcriptomes in mice exposed to multi-walled carbon nanotubes

Pulmonary exposure to multi-walled carbon nanotubes (MWCNT) causes inflammation, fibroproliferation, immunotoxicity, and systemic responses in rodents. However, the search for representative biomarkers of exposure is an ongoing endeavor. Whole blood gene expression profiling is a promising new approach for the identification of novel disease biomarkers. We asked if the whole blood transcriptome reflects pathology-specific changes in lung gene expression caused by MWCNT. To answer this question, we performed mRNA sequencing analysis of the whole blood and lung in mice administered MWCNT or vehicle solution via pharyngeal aspiration and sacrificed 56 days later. The pattern of lung mRNA expression as determined using Ingenuity Pathway Analysis (IPA) was indicative of continued inflammation, immune cell trafficking, phagocytosis, and adaptive immune responses. Simultaneously, innate immunity-related transcripts (Plunc, Bpifb1, Reg3g) and cancer-related pathways were downregulated. IPA analysis of the differentially expressed genes in the whole blood suggested increased hematopoiesis, predicted activation of cancer/tumor development pathways, and atopy. There were several common upregulated genes between whole blood and lungs, important for adaptive immune responses: Cxcr1, Cd72, Sharpin, and Slc11a1. Trim24, important for T_H2 cell effector function, was downregulated in both datasets. Hla-dqa1 mRNA was upregulated in the lungs and downregulated in the blood, as was Lilrb4, which controls the reactivity of immune response. "Cancer" disease category had opposing activation status in the two datasets, while the only commonality was "Hypersensitivity". Transcriptome changes occurring in the lungs did not produce a completely replicable pattern in whole blood; however, specific systemic responses may be shared between transcriptomic profiles.

Ontology-driven integrative analysis of omics data through Onassis

Public repositories of large-scale omics datasets represent a valuable resource for researchers. In fact, data re-analysis can either answer novel questions or provide critical data able to complement in-house experiments. However, despite the development of standards for the compilation of metadata, the identification and organization of samples still constitutes a major bottleneck hampering data reuse. We introduce Onassis, an R package within the Bioconductor environment providing key functionalities of Natural Language Processing (NLP) tools. Leveraging biomedical ontologies, Onassis greatly simplifies the association of samples from large-scale repositories to their representation in terms of ontology-based annotations. Moreover, through the use of semantic similarity measures, Onassis hierarchically organizes the datasets of interest, thus supporting the semantically aware analysis of the corresponding omics data. In conclusion, Onassis leverages NLP techniques, biomedical ontologies, and the R statistical framework, to identify, relate, and analyze datasets from public repositories. The tool was tested on various large-scale datasets, including compendia of gene expression, histone marks, and DNA methylation, illustrating how it can facilitate the integrative analysis of various omics data.

Common Gene Expression Patterns in Environmental Model Organisms Exposed to Engineered Nanomaterials: A Meta-Analysis

The use of omics is gaining importance in the field of nanoecotoxicology; an increasing number of studies are aiming to investigate the effects and modes of action of engineered nanomaterials (ENMs) in this way. However, a systematic synthesis of the outcome of such studies regarding common responses and toxicity pathways is currently lacking. We developed an R-scripted computational pipeline to perform reanalysis and functional analysis of relevant transcriptomic data sets using a common approach, independent from the ENM type, and across different organisms, including Arabidopsis thaliana, Caenorhabditis elegans, and Danio rerio. Using the pipeline that can semiautomatically process data from different microarray technologies, we were able to determine the most common molecular mechanisms of nanotoxicity across extremely variable data sets. As expected, we found known mechanisms, such as interference with energy generation, oxidative stress, disruption of DNA synthesis, and activation of DNA-repair but also discovered that some less-described molecular responses to ENMs, such as DNA/RNA methylation, protein folding, and interference with neurological functions, are present across the different studies. Results were visualized in radar charts to assess toxicological response patterns allowing the comparison of different organisms and ENM types. This can be helpful to retrieve ENM-related hazard information and thus fill knowledge gaps in a comprehensive way in regard to the molecular underpinnings and mechanistic understanding of nanotoxicity.

Microglia Actively Remodel Adult Hippocampal Neurogenesis through the Phagocytosis Secretome

During adult hippocampal neurogenesis, most newborn cells undergo apoptosis and are rapidly phagocytosed by resident microglia to prevent the spillover of intracellular contents. Here, we propose that phagocytosis is not merely passive corpse removal but has an active role in maintaining neurogenesis. First, we found that neurogenesis was disrupted in male and female mice chronically deficient for two phagocytosis pathways: the purinergic receptor P2Y12, and the tyrosine kinases of the TAM family Mer tyrosine kinase (MerTK)/Axl. In contrast, neurogenesis was transiently increased in mice in which MerTK expression was conditionally downregulated. Next, we performed a transcriptomic analysis of the changes induced by phagocytosis in microglia in vitro and identified genes involved in metabolism, chromatin remodeling, and neurogenesis-related functions. Finally, we discovered that the secretome of phagocytic microglia limits the production of new neurons both in vivo and in vitro Our data suggest that microglia act as a sensor of local cell death, modulating the balance between proliferation and survival in the neurogenic niche through the phagocytosis secretome, thereby supporting the long-term maintenance of adult hippocampal neurogenesis.SIGNIFICANCE STATEMENT Microglia are the brain professional phagocytes and, in the adult hippocampal neurogenic niche, they remove newborn cells naturally undergoing apoptosis. Here we show that phagocytosis of apoptotic cells triggers a coordinated transcriptional program that alters their secretome, limiting neurogenesis both in vivo and in vitro In addition, chronic phagocytosis disruption in mice deficient for receptors P2Y12 and MerTK/Axl reduces adult hippocampal neurogenesis. In contrast, inducible MerTK downregulation transiently increases neurogenesis, suggesting that microglial phagocytosis provides a negative feedback loop that is necessary for the long-term maintenance of adult hippocampal neurogenesis. Therefore, we speculate that the effects of promoting engulfment/degradation of cell debris may go beyond merely removing corpses to actively promoting regeneration in development, aging, and neurodegenerative diseases.

Comparative Metabolic Network Flux Analysis to Identify Differences in Cellular Metabolism

Metabolic network flux analysis uses genome-scale metabolic reconstructions to integrate transcriptomics, proteomics, and/or metabolomics data to allow for comprehensive interpretation of genotype to metabolic phenotype relationships. The compilation of many Constraint-based model analysis methods into one MATLAB package, the COBRAtoolbox, has opened the possibility of using these methods to the many biologists with some knowledge of the commonly used statistical program, MATLAB. Here we outline the steps required to take a published genome-scale metabolic reconstruction and interrogate its consistency and biological feasibility. Subsequently, we demonstrate how mRNA expression data and metabolomics data, relating to one or more cell types or biological contexts, can be applied to constrain and generate metabolic models descriptive of metabolic flux phenotypes. Finally, we describe the comparison of the resulting models and model outputs with the aim of identifying metabolic biomarkers and changes in cellular metabolism.

Understanding the Molecular Mechanisms of Asthma through Transcriptomics

The transcriptome represents the complete set of RNA transcripts that are produced by the genome under a specific circumstance or in a specific cell. High-throughput methods, including microarray and bulk RNA sequencing, as well as recent advances in biostatistics based on machine learning approaches provides a quick and effective way of identifying novel genes and pathways related to asthma, which is a heterogeneous disease with diverse pathophysiological mechanisms. In this manuscript, we briefly review how to analyze transcriptome data and then provide a summary of recent transcriptome studies focusing on asthma pathogenesis and asthma drug responses. Studies reviewed here are classified into 2 classes based on the tissues utilized: blood and airway cells.

Autoantibody testing by enzyme-linked immunosorbent assay-a case in which the solid phase decides on success and failure

BACKGROUND

The enzyme-linked immunosorbent assay (ELISA) is an indispensable tool for clinical diagnostics to identify or differentiate diseases such as autoimmune illnesses, but also to monitor their progression or control the efficacy of drugs. One use case of ELISA is to differentiate between different states (e.g. healthy vs. diseased). Another goal is to quantitatively assess the biomarker in question, like autoantibodies. Thus, the ELISA technology is used for the discovery and verification of new autoantibodies, too. Of key interest, however, is the development of immunoassays for the sensitive and specific detection of such biomarkers at early disease stages. Therefore, users have to deal with many parameters, such as buffer systems or antigen-autoantibody interactions, to successfully establish an ELISA. Often, fine-tuning like testing of several blocking substances is performed to yield high signal-to-noise ratios.

METHODS

We developed an ELISA to detect IgA and IgG autoantibodies against chitinase-3-like protein 1 (CHI3L1), a newly identified autoantigen in inflammatory bowel disease (IBD), in the serum of control and disease groups (n = 23, respectively). Microwell plates with different surface modifications (PolySorp and MaxiSorp coating) were tested to detect reproducibility problems.

RESULTS

We found a significant impact of the surface properties of the microwell plates. IgA antibody reactivity was significantly lower, since it was in the range of background noise, when measured on MaxiSorp coated plates (p < 0.0001). The IgG antibody reactivity did not differ on the diverse plates, but the plate surface had a significant influence on the test result (p = 0.0005).

CONCLUSION

With this report, we want to draw readers' attention to the properties of solid phases and their effects on the detection of autoantibodies by ELISA. We want to sensitize the reader to the fact that the choice of the wrong plate can lead to a false negative test result, which in turn has serious consequences for the discovery of autoantibodies.

Microarray-Based Quality Assessment as a Supporting Criterion for de novo Transcriptome Assembly Selection

RNA-Sequencing and de novo assembly have enabled the analysis of species with non-available reference transcriptomes, although intrinsic features (biological and technical) induce errors in the reconstruction. A strategy to resolve these errors consists of varying assembling process parameters to generate multiple reconstructions. However, the best assembly selection remains a challenge. Quantitative metrics for quality assessment have been inconsistent when compared with pertinent references. In this paper, a criterion for supporting assembly selection based on mapping DNA microarray hybridized probes to assembly sets is proposed. Mouse and fruit fly RNA-Seq datasets were assembled with standard de novo procedures. Quality assessment was estimated using quantitative metrics and the proposed criterion. The assembly that best mapped to the available reference transcriptomes of these model species provided the highest quality assembly. The hybridized probes identified the best assemblies, whereas quantitative metrics remained inconsistent. For example, subtle probe mapping difference of 0.25 percent, but statistically significant (ANOVA, p < 0.05), enabled the assembly selection that led to identify 3,719 more contigs and led to 1,049 further mapped contigs to the mouse reference transcriptome. The microarray data availability for non-model species makes the proposed criterion suitable for quality assessment of multiple de novo assembly strategies.

FAIR Principles: Interpretations and Implementation Considerations

The FAIR principles have been widely cited, endorsed and adopted by a broad range of stakeholders since their publication in 2016. By intention, the 15 FAIR guiding principles do not dictate specific technological implementations, but provide guidance for improving Findability, Accessibility, Interoperability and Reusability of digital resources. This has likely contributed to the broad adoption of the FAIR principles, because individual stakeholder communities can implement their own FAIR solutions. However, it has also resulted in inconsistent interpretations that carry the risk of leading to incompatible implementations. Thus, while the FAIR principles are formulated on a high level and may be interpreted and implemented in different ways, for true interoperability we need to support convergence in implementation choices that are widely accessible and (re)-usable. We introduce the concept of FAIR implementation considerations to assist accelerated global participation and convergence towards accessible, robust, widespread and consistent FAIR implementations. Any self-identified stakeholder community may either choose to reuse solutions from existing implementations, or when they spot a gap, accept the challenge to create the needed solution, which, ideally, can be used again by other communities in the future. Here, we provide interpretations and implementation considerations (choices and challenges) for each FAIR principle.

Recommendations for the collection and use of multiplexed functional data for clinical variant interpretation

Variants of uncertain significance represent a massive challenge to medical genetics. Multiplexed functional assays, in which the functional effects of thousands of genomic variants are assessed simultaneously, are increasingly generating data that can be used as additional evidence for or against variant pathogenicity. Such assays have the potential to resolve variants of uncertain significance, thereby increasing the clinical utility of genomic testing. Existing standards from the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) and new guidelines from the Clinical Genome Resource (ClinGen) establish the role of functional data in variant interpretation, but do not address the specific challenges or advantages of using functional data derived from multiplexed assays. Here, we build on these existing guidelines to provide recommendations to experimentalists for the production and reporting of multiplexed functional data and to clinicians for the evaluation and use of such data. By following these recommendations, experimentalists can produce transparent, complete, and well-validated datasets that are primed for clinical uptake. Our recommendations to clinicians and diagnostic labs on how to evaluate the quality of multiplexed functional datasets, and how different datasets could be incorporated into the ACMG/AMP variant-interpretation framework, will hopefully clarify whether and how such data should be used. The recommendations that we provide are designed to enhance the quality and utility of multiplexed functional data, and to promote their judicious use.

Ten challenges for EEG-based affective computing

The emerging field of affective computing focuses on enhancing computers’ ability to understand and appropriately respond to people’s affective states in human-computer interactions, and has revealed significant potential for a wide spectrum of applications. Recently, the electroencephalography (EEG) based affective computing has gained increasing interest for its good balance between mechanistic exploration and real-world practical application. The present work reviewed ten theoretical and operational challenges for the existing affective computing researches from an interdisciplinary perspective of information technology, psychology, and neuroscience. On the theoretical side, we suggest that researchers should be well aware of the limitations of the commonly used emotion models, and be cautious about the widely accepted assumptions on EEG-emotion relationships as well as the transferability of findings based on different research paradigms. On the practical side, we propose several operational recommendations for the challenges about data collection, feature extraction, model implementation, online system design, as well as the potential ethical issues. The present review is expected to contribute to an improved understanding of EEG-based affective computing and promote further applications.

The minimum information required for a glycomics experiment (MIRAGE) project: LC guidelines

The Minimum Information Required for a Glycomics Experiment (MIRAGE) is an initiative created by experts in the fields of glycobiology, glycoanalytics and glycoinformatics to design guidelines that improve the reporting and reproducibility of glycoanalytical methods. Previously, the MIRAGE Commission has published guidelines for describing sample preparation methods and the reporting of glycan array and mass spectrometry techniques and data collections. Here, we present the first version of guidelines that aim to improve the quality of the reporting of liquid chromatography (LC) glycan data in the scientific literature. These guidelines cover all aspects of instrument setup and modality of data handling and manipulation and is cross-linked with other MIRAGE recommendations. The most recent version of the MIRAGE-LC guidelines is freely available at the MIRAGE project website doi:10.3762/mirage.4.

Bacillus amyloliquefaciens MBI600 differentially induces tomato defense signaling pathways depending on plant part and dose of application

The success of Bacillus amyloliquefaciens as a biological control agent relies on its ability to outgrow plant pathogens. It is also thought to interact with its plant host by inducing systemic resistance. In this study, the ability of B. amyloliquefaciens MBI600 to elicit defense (or other) responses in tomato seedlings and plants was assessed upon the expression of marker genes and transcriptomic analysis. Spray application of Serifel, a commercial formulation of MBI600, induced responses in a dose-dependent manner. Low dosage primed plant defense by activation of SA-responsive genes. Suggested dosage induced defense by mediating synergistic cross-talk between JA/ET and SA-signaling. Saturation of tomato roots or leaves with MBI600 elicitors activated JA/ET signaling at the expense of SA-mediated responses. The complex signaling network that is implicated in MBI600-tomato seedling interactions was mapped. MBI600 and flg22 (a bacterial flagellin peptide) elicitors induced, in a similar manner, biotic and abiotic stress responses by the coordinated activation of genes involved in JA/ET biosynthesis as well as hormone and redox signaling. This is the first study to suggest the activation of plant defense following the application of a commercial microbial formulation under conditions of greenhouse crop production.

Gene Expression Profiles Induced by High-dose Ionizing Radiation in MDA-MB-231 Triple-negative Breast Cancer Cell Line

BACKGROUND/AIM

Radiation therapy (RT) represents a therapeutic option in breast cancer (BC). Even if a great number of BC patients receive RT, not all of them report benefits, due to radioresistance that gets activated through several factors, such as the hormone receptor status. Herein, we analyzed the gene expression profiles (GEP) induced by RT in triple-negative BC (TNBC) MDA-MB-231, to study signalling networks involved in radioresistance.

MATERIALS AND METHODS

GEP of MDA-MB-231 BC cells treated with a high dose of radiation, went through cDNA microarray analysis. In addition, to examine the cellular effects induced by RT, analyses of morphology and clonogenic evaluation were also conducted.

RESULTS

A descriptive report of GEP and pathways induced by IR is reported from our microarray data. Moreover, the MDA-MB-231 Radioresistent Cell Fraction (RCF) selected, included specific molecules able to drive radioresistance.

CONCLUSION

In summary, our data highlight, the RT response of TNBC MDA-MB-231 cell line at a transcriptional level, in terms of activating radioresistance in these cells, as a model of late-stage BC.

The CCN1 (CYR61) protein promotes skin growth by enhancing epithelial-mesenchymal transition during skin expansion

The skin expansion technique is widely used to induce skin growth for large-scale skin deformity reconstruction. However, the capacity for skin expansion is limited and searching for ways to improve the expansion efficiency is a challenge. In this study, we aimed to explore the possible mechanism of skin expansion and to find a potential therapeutic target on promoting skin growth. We conducted weighted gene coexpression network analysis (WGCNA) of microarray data generated from rat skin expansion and found CCN1 (CYR61) to be the central hub gene related to epithelial-mesenchymal transition (EMT). CCN1 up-regulation was confirmed in human and rat expanded skin and also in mechanically stretched rat keratinocytes, together with acquired mesenchymal phenotype. After CCN1 stimulation on keratinocytes, cell proliferation was promoted and partial EMT was induced by activating β-catenin pathway. Treatment of CCN1 protein could significantly increase the flap thickness, improve the blood supply and restore the structure in a rat model of skin expansion, whereas inhibition of CCN1 through shRNA interference could dramatically reduce the efficiency of skin expansion. Our findings demonstrate that CCN1 plays a crucial role in skin expansion and that CCN1 may serve as a potential therapeutic target to promote skin growth and improve the efficiency of skin expansion.

Available Software for Meta-analyses of Genome-wide Expression Studies

Advances in transcriptomic methods have led to a large number of published Genome-Wide Expression Studies (GWES), in humans and model organisms. For several years, GWES involved the use of microarray platforms to compare genome-expression data for two or more groups of samples of interest. Meta-analysis of GWES is a powerful approach for the identification of differentially expressed genes in biological topics or diseases of interest, combining information from multiple primary studies. In this article, the main features of available software for carrying out meta-analysis of GWES have been reviewed and seven packages from the Bioconductor platform and five packages from the CRAN platform have been described. In addition, nine previously described programs and four online programs are reviewed. Finally, advantages and disadvantages of these available programs and proposed key points for future developments have been discussed.

ADGRL4/ELTD1 Silencing in Endothelial Cells Induces ACLY and SLC25A1 and Alters the Cellular Metabolic Profile

Adhesion G Protein-Coupled Receptor L4 (ADGRL4/ELTD1) is an endothelial cell adhesion G protein-coupled receptor (aGPCR) which regulates physiological and tumour angiogenesis, providing an attractive target for anti-cancer therapeutics. To date, ADGRL4/ELTD1's full role and mechanism of function within endothelial biology remains unknown, as do its ligand(s). In this study, ADGRL4/ELTD1 silencing, using two independent small interfering RNAs (siRNAs), was performed in human umbilical vein endothelial cells (HUVECS) followed by transcriptional profiling, target gene validation, and metabolomics using liquid chromatography-mass spectrometry in order to better characterise ADGRL4/ELTD1's role in endothelial cell biology. We show that ADGRL4/ELTD1 silencing induced expression of the cytoplasmic metabolic regulator ATP Citrate Lyase (ACLY) and the mitochondria-to-cytoplasm citrate transporter Solute Carrier Family 25 Member 1 (SLC25A1) but had no apparent effect on pathways downstream of ACLY (fatty acid and cholesterol synthesis or acetylation). Silencing induced KIT expression and affected the Notch signalling pathway, upregulating Delta Like Canonical Notch Ligand 4 (DLL4) and suppressing Jagged Canonical Notch Ligand 1 (JAG1) and Hes Family BHLH Transcription Factor 2 (HES2). The effect of ADGRL4/ELTD1 silencing on the cellular metabolic profile was modest but several metabolites were significantly affected. Cis-aconitic acid, uridine diphosphate (UDP)-glucoronate, fructose 2,6-diphosphate, uridine 5-diphosphate, and aspartic acid were all elevated as a result of silencing and phosphocreatine, N-acetylglutamic acid, taurine, deoxyadenosine triphosphate, and cytidine monophosphate were depleted. Metabolic pathway analysis implicated ADGRL4/ELTD1 in pyrimidine, amino acid, and sugar metabolism. In summary, this study shows that ADGRL4/ELTD1 impacts core components of endothelial metabolism and regulates genes involved in endothelial differentiation/homeostasis and Notch signalling.

TACITuS: transcriptomic data collector, integrator, and selector on big data platform

BACKGROUND

Several large public repositories of microarray datasets and RNA-seq data are available. Two prominent examples include ArrayExpress and NCBI GEO. Unfortunately, there is no easy way to import and manipulate data from such resources, because the data is stored in large files, requiring large bandwidth to download and special purpose data manipulation tools to extract subsets relevant for the specific analysis.

RESULTS

TACITuS is a web-based system that supports rapid query access to high-throughput microarray and NGS repositories. The system is equipped with modules capable of managing large files, storing them in a cloud environment and extracting subsets of data in an easy and efficient way. The system also supports the ability to import data into Galaxy for further analysis.

CONCLUSIONS

TACITuS automates most of the pre-processing needed to analyze high-throughput microarray and NGS data from large publicly-available repositories. The system implements several modules to manage large files in an easy and efficient way. Furthermore, it is capable deal with Galaxy environment allowing users to analyze data through a user-friendly interface.

Driver gene alterations and activated signaling pathways toward malignant progression of gastrointestinal stromal tumors

Mutually exclusive KIT and PDGFRA mutations are considered to be the earliest events in gastrointestinal stromal tumors (GIST), but insufficient for their malignant progression. Herein, we aimed to identify driver genes and signaling pathways relevant to GIST progression. We investigated genetic profiles of 707 driver genes, including mutations, gene fusions, copy number gain or loss, and gene expression for 65 clinical specimens of surgically dissected GIST, consisting of six metastatic tumors and 59 primary tumors from stomach, small intestine, rectum, and esophagus. Genetic alterations included oncogenic mutations and amplification‐dependent expression enhancement for oncogenes (OG), and loss of heterozygosity (LOH) and expression reduction for tumor suppressor genes (TSG). We assigned activated OG and inactivated TSG to 27 signaling pathways, the activation of which was compared between malignant GIST (metastasis and high‐risk GIST) and less malignant GIST (low‐ and very low‐risk GIST). Integrative molecular profiling indicated that a greater incidence of genetic alterations of driver genes was detected in malignant GIST (96%, 22 of 23) than in less malignant GIST (73%, 24 of 33). Malignant GIST samples groups showed mutations, LOH, and aberrant expression dominantly in driver genes associated with signaling pathways of PI3K (PIK3CA, AKT1, and PTEN) and the cell cycle (RB1, CDK4, and CDKN1B). Additionally, we identified potential PI3K‐related genes, the expression of which was upregulated (SNAI1 and TPX2) or downregulated (BANK1) in malignant GIST. Based on our observations, we propose that inhibition of PI3K pathway signals might potentially be an effective therapeutic strategy against malignant progression of GIST.

Deciphering host immunity to malaria using systems immunology

A century of conceptual and technological advances in infectious disease research has changed the face of medicine. However, there remains a lack of effective interventions and a poor understanding of host immunity to the most significant and complex pathogens, including malaria. The development of successful interventions against such intractable diseases requires a comprehensive understanding of host-pathogen immune responses. A major advance of the past decade has been a paradigm switch in thinking from the contemporary reductionist (gene-by-gene or protein-by-protein) view to a more holistic (whole organism) view. Also, a recognition that host-pathogen immunity is composed of complex, dynamic interactions of cellular and molecular components and networks that cannot be represented by any individual component in isolation. Systems immunology integrates the field of immunology with omics technologies and computational sciences to comprehensively interrogate the immune response at a systems level. Herein, we describe the system immunology toolkit and report recent studies deploying systems-level approaches in the context of natural exposure to malaria or controlled human malaria infection. We contribute our perspective on the potential of systems immunity for the rational design and development of effective interventions to improve global public health.

Metabolic response to Parkinson's disease recapitulated by the haploinsufficient diploid yeast cells hemizygous for the adrenodoxin reductase gene

Adrenodoxin reductase, a widely conserved mitochondrial P450 protein, catalyses essential steps in steroid hormone biosynthesis and is highly expressed in the adrenal cortex. The yeast adrenodoxin reductase homolog, Arh1p, is involved in cytoplasmic and mitochondrial iron homeostasis and is required for activity of enzymes containing an Fe-S cluster. In this paper, we investigated the response of yeast to the loss of a single copy of ARH1, an oxidoreductase of the mitochondrial inner membrane, which is among the few mitochondrial proteins that is essential for viability in yeast. The phenotypic, transcriptional, proteomic, and metabolic landscape indicated that Saccharomyces cerevisiae successfully adapted to this loss, displaying an apparently dosage-insensitive cellular response. However, a considered investigation of transcriptional regulation in ARH1-impaired yeast highlighted that a significant hierarchical reorganisation occurred, involving the iron assimilation and tyrosine biosynthetic processes. The interconnected roles of the iron and tyrosine pathways, coupled with oxidative processes, are of interest beyond yeast since they are involved in dopaminergic neurodegeneration associated with Parkinson's disease. The identification of similar responses in yeast, albeit preliminary, suggests that this simple eukaryote could have potential as a model system for investigating the regulatory mechanisms leading to the initiation and progression of early disease responses in humans.

Rag1 immunodeficiency-induced early aging and senescence in zebrafish are dependent on chronic inflammation and oxidative stress

In mammals, recombination activating gene 1 (RAG1) plays a crucial role in adaptive immunity, generating a vast range of immunoglobulins. Rag1^−/− zebrafish (Danio rerio) are viable and reach adulthood without obvious signs of infectious disease in standard nonsterile conditions, suggesting that innate immunity could be enhanced to compensate for the lack of adaptive immunity. By using microarray analysis, we confirmed that the expression of immunity‐ and apoptosis‐related genes was increased in the rag1^−/− fish. This tool also allows us to notice alterations of the DNA repair and cell cycle mechanisms in rag1^−/− zebrafish. Several senescence and aging markers were analyzed. In addition to the lower lifespan of rag1^−/− zebrafish compared to their wild‐type (wt) siblings, rag1^−/− showed a higher incidence of cell cycle arrest and apoptosis, a greater amount of phosphorylated histone H2AX, oxidative stress and decline of the antioxidant mechanisms, an upregulated expression and activity of senescence‐related genes and senescence‐associated β‐galactosidase, respectively, diminished telomere length, and abnormal self‐renewal and repair capacities in the retina and liver. Metabolomic analysis also demonstrated clear differences between wt and rag1^−/− fish, as was the deficiency of the antioxidant metabolite l‐acetylcarnitine (ALCAR) in rag1^−/− fish. Therefore, Rag1 activity does not seem to be limited to V(D)J recombination but is also involved in senescence and aging. Furthermore, we confirmed the senolytic effect of ABT‐263, a known senolytic compound and, for the first time, the potential in vivo senolytic activity of the antioxidant agent ALCAR, suggesting that this metabolite is essential to avoid premature aging.

Tissue-regenerative potential of the secretome of γ-irradiated peripheral blood mononuclear cells is mediated via TNFRSF1B-induced necroptosis

Peripheral blood mononuclear cells (PBMCs) have been shown to produce and release a plethora of pro-angiogenetic factors in response to γ-irradiation, partially accounting for their tissue-regenerative capacity. Here, we investigated whether a certain cell subtype of PBMCs is responsible for this effect, and whether the type of cell death affects the pro-angiogenic potential of bioactive molecules released by γ-irradiated PBMCs. PBMCs and PBMC subpopulations, including CD4⁺ and CD8⁺ T cells, B cells, monocytes, and natural killer cells, were isolated and subjected to high-dose γ-irradiation. Transcriptome analysis revealed subpopulation-specific responses to γ-irradiation with distinct activation of pro-angiogenic pathways, cytokine production, and death receptor signalling. Analysis of the proteins released showed that interactions of the subsets are important for the generation of a pro-angiogenic secretome. This result was confirmed at the functional level by the finding that the secretome of γ-irradiated PBMCs displayed higher pro-angiogenic activity in an aortic ring assay. Scanning electron microscopy and image stream analysis of γ-irradiated PBMCs revealed distinct morphological changes, indicative for apoptotic and necroptotic cell death. While inhibition of apoptosis had no effect on the pro-angiogenic activity of the secretome, inhibiting necroptosis in stressed PBMCs abolished blood vessel sprouting. Mechanistically, we identified tumor necrosis factor (TNF) receptor superfamily member 1B as the main driver of necroptosis in response to γ-irradiation in PBMCs, which was most likely mediated via membrane-bound TNF-α. In conclusion, our study demonstrates that the pro-angiogenic activity of the secretome of γ-irradiated PBMCs requires interplay of different PBMC subpopulations. Furthermore, we show that TNF-dependent necroptosis is an indispensable molecular process for conferring tissue-regenerative activity and for the pro-angiogenic potential of the PBMC secretome. These findings contribute to a better understanding of secretome-based therapies in regenerative medicine.

Implication of transcriptome profiling of spermatozoa for stallion fertility

Poor fertility of breeding stallions is a recognised problem in the equine industry. The aim of the present study was to detect molecular pathways using two groups of stallions that differed in pregnancy rates as well as in the proportion of normal and motile spermatozoa. RNA was isolated from spermatozoa of each stallion and microarray data were analysed to obtain a list of genes for which transcript abundance differed between the groups (P ≤0.05, fold change ≥1.2). In all, there were 437 differentially expressed (DE) genes between the two groups (P ≤ 0.05, fold change ≥1.2). Next, the DE genes were analysed using Database for Annotation, Visualisation, and Integrated Discovery (DAVID). Finally, ingenuity pathways analysis (IPA) was used to identify top biological functions and significant canonical pathways associated with the DE genes. Analysis using the DAVID database showed significant enrichment in the gene ontology (GO) term 'RNA binding' (P=0.05) and in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway cytokine-cytokine receptor interaction (P=0.02). Furthermore, IPA analysis showed interconnected biological functions and canonical pathways involved in the regulation of spermatogenesis and male fertility. In addition, significantly enriched metabolic pathways were identified. In conclusion, the present study has identified, for the first time, molecular processes in stallion spermatozoa that could be associated with stallion fertility.

Perspective: Dimensions of the scientific method

The scientific method has been guiding biological research for a long time. It not only prescribes the order and types of activities that give a scientific study validity and a stamp of approval but also has substantially shaped how we collectively think about the endeavor of investigating nature. The advent of high-throughput data generation, data mining, and advanced computational modeling has thrown the formerly undisputed, monolithic status of the scientific method into turmoil. On the one hand, the new approaches are clearly successful and expect the same acceptance as the traditional methods, but on the other hand, they replace much of the hypothesis-driven reasoning with inductive argumentation, which philosophers of science consider problematic. Intrigued by the enormous wealth of data and the power of machine learning, some scientists have even argued that significant correlations within datasets could make the entire quest for causation obsolete. Many of these issues have been passionately debated during the past two decades, often with scant agreement. It is proffered here that hypothesis-driven, data-mining-inspired, and "allochthonous" knowledge acquisition, based on mathematical and computational models, are vectors spanning a 3D space of an expanded scientific method. The combination of methods within this space will most certainly shape our thinking about nature, with implications for experimental design, peer review and funding, sharing of result, education, medical diagnostics, and even questions of litigation.

Evaluating Chemicals for Thyroid Disruption: Opportunities and Challenges with in Vitro Testing and Adverse Outcome Pathway Approaches

BACKGROUND

Extensive clinical and experimental research documents the potential for chemical disruption of thyroid hormone (TH) signaling through multiple molecular targets. Perturbation of TH signaling can lead to abnormal brain development, cognitive impairments, and other adverse outcomes in humans and wildlife. To increase chemical safety screening efficiency and reduce vertebrate animal testing, in vitro assays that identify chemical interactions with molecular targets of the thyroid system have been developed and implemented.

OBJECTIVES

We present an adverse outcome pathway (AOP) network to link data derived from in vitro assays that measure chemical interactions with thyroid molecular targets to downstream events and adverse outcomes traditionally derived from in vivo testing. We examine the role of new in vitro technologies, in the context of the AOP network, in facilitating consideration of several important regulatory and biological challenges in characterizing chemicals that exert effects through a thyroid mechanism.

DISCUSSION

There is a substantial body of knowledge describing chemical effects on molecular and physiological regulation of TH signaling and associated adverse outcomes. Until recently, few alternative nonanimal assays were available to interrogate chemical effects on TH signaling. With the development of these new tools, screening large libraries of chemicals for interactions with molecular targets of the thyroid is now possible. Measuring early chemical interactions with targets in the thyroid pathway provides a means of linking adverse outcomes, which may be influenced by many biological processes, to a thyroid mechanism. However, the use of in vitro assays beyond chemical screening is complicated by continuing limits in our knowledge of TH signaling in important life stages and tissues, such as during fetal brain development. Nonetheless, the thyroid AOP network provides an ideal tool for defining causal linkages of a chemical exerting thyroid-dependent effects and identifying research needs to quantify these effects in support of regulatory decision making. https://doi.org/10.1289/EHP5297.

Gene Expression Maps in Plants: Current State and Prospects

For many years, progress in the identification of gene functions has been based on classical genetic approaches. However, considerable recent omics developments have brought to the fore indirect but high-resolution methods of gene function identification such as transcriptomics, proteomics, and metabolomics. A transcriptome map is a powerful source of functional information and the result of the genome-wide expression analysis of a broad sampling of tissues and/or organs from different developmental stages and/or environmental conditions. In plant science, the application of transcriptome maps extends from the inference of gene regulatory networks to evolutionary studies. However, only some of these data have been integrated into databases, thus enabling analyses to be conducted without raw data; without this integration, extensive data preprocessing is required, which limits data usability. In this review, we summarize the state of plant transcriptome maps, analyze the problems associated with the combined analysis of large-scale data from various studies, and outline possible solutions to these problems.