Variation-preserving normalization unveils blind spots in gene expression profiling

TiO2 nanoparticles' library toxicity (UV and non-UV exposure) - High-throughput in vivo transcriptomics reveals mechanisms

The hazards of nanomaterials/nanoparticles (NMs/NPs) are mostly assessed using individual NMs, and a more systematic approach, using many NMs, is needed to evaluate its risks in the environment. Libraries of NMs, with a range of identified different but related characters/descriptors allow the comparison of effects across many NMs. The effects of a custom designed Fe-doped TiO₂ NMs library containing 11 NMs was assessed on the soil model Enchytraeus crypticus (Oligochaeta), both with and without UV (standard fluorescent) radiation. Effects were analyzed at organism (phenotypic, survival and reproduction) and gene expression level (transcriptomics, high-throughput 4x44K microarray) to understand the underlying mechanisms. A total of 48 microarrays (20 test conditions) were done plus controls (UV and non-UV). Unique mechanisms induced by TiO₂ NPs exposure included the impairment in RNA processing for TiO₂_10nm, or deregulated apoptosis for 2%FeTiO₂_10nm. Strikingly apparent was the size dependent effects such as induction of reproductive effects via smaller TiO₂ NPs (≤12 nm) - embryo interaction, while larger particles (27 nm) caused reproductive effects through different mechanisms. Also, phagocytosis was affected by 12 and 27 nm NPs, but not by ≤11 nm. The organism level study shows the integrated response, i.e. the result after a cascade of events. While uni-cell models offer key mechanistic information, we here deliver a combined biological system level (phenotype and genotype), seldom available, especially for environmental models.

Using Machine Learning to make nanomaterials sustainable

Sustainable development is a key challenge for contemporary human societies; failure to achieve sustainability could threaten human survival. In this review article, we illustrate how Machine Learning (ML) could support more sustainable development, covering the basics of data gathering through each step of the Environmental Risk Assessment (ERA). The literature provides several examples showing how ML can be employed in most steps of a typical ERA.A key observation is that there are currently no clear guidance for using such autonomous technologies in ERAs or which standards/checks are required. Steering thus seems to be the most important task for supporting the use of ML in the ERA of nano- and smart-materials. Resources should be devoted to developing a strategy for implementing ML in ERA with a strong emphasis on data foundations, methodologies, and the related sensitivities/uncertainties. We should recognise historical errors and biases (e.g., in data) to avoid embedding them during ML programming.

On virus and nanomaterials - Lessons learned from the innate immune system - ACE activation in the invertebrate model Enchytraeus crypticus

Current human research on COVID-19 - SARS-CoV-2 (Severe Acute Respiratory Syndrome-Corona Virus) showed that ACE2 (Angiotensin Converting Enzyme 2) is a functional receptor to which the spike proteins attach. Invertebrates have been exposed to a wide array of threats for millennia and their immune system has evolved to deal with these efficiently. The annelid Enchytraeus crypticus, a standard ecotoxicological species, is an invertebrate species where extensive mechanisms of response studies are available, covering all levels from gene to population responses. Nanomaterials (NMs) are often perceived as invaders (e.g. virus) and can enter the cell covered by a corona, triggering similar responses. We created a database on E. crypticus ACE gene expression, aiming to analyse the potential knowledge transfer between invertebrates and vertebrates. Total exposure experiments sum 87 stress conditions for 18 different nanomaterials (NMs). ACE expression following TiO2 NM exposure was clearly different from other NMs showing a clear (6-7 fold) ACE down-regulation, not observed for any other NMs. Other NMs, notably Ag NMs, and to some extent Cu NMs, caused ACE up-regulation (up to 4 fold). The extensive knowledge from response to NMs can support the immuno-research community, especially to develop therapies for virus that trigger the innate immune system.

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

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

Annelid genomes: Enchytraeus crypticus, a soil model for the innate (and primed) immune system

Enchytraeids (Annelida) are soil invertebrates with worldwide distribution that have served as ecotoxicology models for over 20 years. We present the first high-quality reference genome of Enchytraeus crypticus, assembled from a combination of Pacific Bioscience single-molecule real-time and Illumina sequencing platforms as a 525.2 Mbp genome (910 gapless scaffolds and 18,452 genes). We highlight isopenicillin, acquired by horizontal gene transfer and conferring antibiotic function. Significant gene family expansions associated with regeneration (long interspersed nuclear elements), the innate immune system (tripartite motif-containing protein) and response to stress (cytochrome P450) were identified. The ACE (Angiotensin-converting enzyme) - a homolog of ACE2, which is involved in the coronavirus SARS-CoV-2 cell entry - is also present in E. crypticus. There is an obvious potential of using E. crypticus as a model to study interactions between regeneration, the innate immune system and aging-dependent decline.

Identification of conserved transcriptome features between humans and Drosophila in the aging brain utilizing machine learning on combined data from the NIH Sequence Read Archive

Aging is universal, yet characterizing the molecular changes that occur in aging which lead to an increased risk for neurological disease remains a challenging problem. Aging affects the prefrontal cortex (PFC), which governs executive function, learning, and memory. Previous sequencing studies have demonstrated that aging alters gene expression in the PFC, however the extent to which these changes are conserved across species and are meaningful in neurodegeneration is unknown. Identifying conserved, age-related genetic and morphological changes in the brain allows application of the wealth of tools available to study underlying mechanisms in model organisms such as Drosophila melanogaster. RNA sequencing data from human PFC and fly heads were analyzed to determine conserved transcriptome signatures of age. Our analysis revealed that expression of 50 conserved genes can accurately determine age in Drosophila (R2 = 0.85) and humans (R2 = 0.46). These transcriptome signatures were also able to classify Drosophila into three age groups with a mean accuracy of 88% and classify human samples with a mean accuracy of 69%. Overall, this work identifies 50 highly conserved aging-associated genetic changes in the brain that can be further studied in model organisms and demonstrates a novel approach to uncovering genetic changes conserved across species from multi-study public databases.

Significance tests for analyzing gene expression data with small sample sizes

MOTIVATION

Under two biologically different conditions, we are often interested in identifying differentially expressed genes. It is usually the case that the assumption of equal variances on the two groups is violated for many genes where a large number of them are required to be filtered or ranked. In these cases, exact tests are unavailable and the Welch's approximate test is most reliable one. The Welch's test involves two layers of approximations: approximating the distribution of the statistic by a t-distribution, which in turn depends on approximate degrees of freedom. This study attempts to improve upon Welch's approximate test by avoiding one layer of approximation.

RESULTS

We introduce a new distribution that generalizes the t-distribution and propose a Monte Carlo based test that uses only one layer of approximation for statistical inferences. Experimental results based on extensive simulation studies show that the Monte Carol based tests enhance the statistical power and performs better than Welch's t-approximation, especially when the equal variance assumption is not met and the sample size of the sample with a larger variance is smaller. We analyzed two gene-expression datasets, namely the childhood acute lymphoblastic leukemia gene-expression dataset with 22 283 genes and Golden Spike dataset produced by a controlled experiment with 13 966 genes. The new test identified additional genes of interest in both datasets. Some of these genes have been proven to play important roles in medical literature.

AVAILABILITY AND IMPLEMENTATION

R scripts and the R package mcBFtest is available in CRAN and to reproduce all reported results are available at the GitHub repository, https://github.com/iullah1980/MCTcodes.

SUPPLEMENTARY INFORMATION

Supplementary data is available at Bioinformatics online.

High-throughput transcriptomics: Insights into the pathways involved in (nano) nickel toxicity in a key invertebrate test species

Nickel nanoparticles (NiNPs) have an estimated production of ca. 20 tons per year in the US. Nickel has been risk-assessed for long in Europe, but not NiNPs, hence the concern for the environment. In the present study, we focused on investigating the mechanisms of toxicity of NiNPs and the comparison to NiNO₃. The high-throughput microarray for the soil ecotox model Enchytraeus crypticus (Oligochaeta) was used. To anchor gene to phenotype effect level, organisms were exposed to reproduction effect concentrations EC20 and EC50, for 3 and 7 days. Results showed commonly affected pathways between NiNPs and NiNO₃, including increase in proteolysis, apoptosis and inflammatory response, and interference with the nervous system. Mechanisms unique to NiNO₃ were also observed (e.g. glutathione synthesis). No specific mechanisms for NiNPs were found, which could indicate that longer exposure period (>7 days) is required to capture the peak response to NiNPs. A mechanisms scheme is assembled, showing both common and unique mechanisms to NiNO₃ and NiNPs, providing an important framework for further, more targeted, studies.

High-throughput gene expression in soil invertebrate embryos - Mechanisms of Cd toxicity in Enchytraeus crypticus

Gene expression can vary with the organisms' life stage. It is known that embryos can be more sensitive to toxicant exposure, as previously demonstrated for Enchytraeus crypticus (Oligochaeta) exposed to cadmium (Cd), known to cause embryotoxicity and hatching delay. It was shown that Ca enters embryos via the L-type Ca channels in the cocoon membrane, this being affected in Cd exposed embryos (Cd-Ca competition is well-known). In the present study, the embryotoxic mechanisms of Cd were studied via high-throughput gene expression for E. crypticus. Cocoons (1-2 days old), instead of the adult organism, were exposed in Cd spiked LUFA 2.2 soil during 1 day. Results showed that Cd affected Ca homeostasis which is implicated in several other molecular processes. Several of the major modulators of Cd toxicity (e.g., impaired gene expression, cell cycle arrest, DNA and mitochondrial damage) were identified in the embryos showing its relevancy as a model in ecotoxicogenomics. The draft Adverse Outcome Pathway was improved. Previously was hypothesized that gene regulation mechanisms were activated to synthesize more Ca channel proteins - this was confirmed here. Further, novel evidences were that, besides the extracellular competition, Cd competes intracellularly which causes a reduction in Ca efflux, and potentiates Cd embryotoxicity.

Mechanisms of (photo)toxicity of TiO2 nanomaterials (NM103, NM104, NM105): using high-throughput gene expression in Enchytraeus crypticus

Titanium dioxide (TiO2) based nanomaterials (NMs) are among the most produced NMs worldwide. When irradiated with light, particularly UV, TiO2 is photoactive, a property that is explored for several purposes. There are an increasing number of reports on the negative effects of photoactivated TiO2 on non-target organisms. We have here studied the effect of a suite of reference type TiO2 NMs (i.e. NM103, NM104, and NM105 and compared these to the bulk) with and without UV radiation to the oligochaete Enchytraeus crypticus. High-throughput gene expression was used to assess the molecular mechanisms, while also anchoring it to the known effects at the organism level (i.e., reproduction). Results showed that the photoactivity of TiO2 (UV exposed) played a major role in enhancing TiO2 toxicity, activating the transcription of oxidative stress, lysosome damage and apoptosis mechanisms. For non-UV activated TiO2, where toxicity at the organism level (reproduction) was lower, results showed potential for long-term effects (i.e., mutagenic and epigenetic). NM specific mechanisms were identified: NM103 affected transcription and translation, NM104_UV negatively affected the reproductive system/organs, and NM105_UV activated superoxide anion response. Results provided mechanistic information on UV-related phototoxicity of TiO2 materials and evidence for the potential long-term effects.

Identifying conserved UV exposure genes and mechanisms

Studies have been showing how changes in ultraviolet (UV) affect the terrestrial system, mostly focusing on higher plants and indirect effects, e.g. UV changed food quality/decomposition. Much less attention has been given to direct effect on terrestrial species, although the negative effects have been recognized for some earthworms. Further, the actual mechanisms of UV toxicity to soil invertebrates are even less understood. We here studied the effect of UV on the soil oligochaete Enchytraeus crypticus, and attempted to identify the possible mechanisms of toxicity using high-throughput gene expression. Applying a UV dose equivalent to UV during the winter months in northern Europe we observed an 80% decrease in reproduction. For these organisms, approximately 5% of the genes were differentially expressed. Among the observations was an activation of the DNA repair mechanisms, nucleotide excision repair, which correlated with survival of the organisms. An observed repressing of apoptosis seems to have deleterious effects (e.g. because it may lead to the accumulation of aberrant cells) leading to a decline in reproduction. The mechanisms activated by UV were similar to those mechanisms activated in humans, showing conservation across species.

High-throughput tool to discriminate effects of NMs (Cu-NPs, Cu-nanowires, CuNO3, and Cu salt aged): transcriptomics in Enchytraeus crypticus

The current testing of nanomaterials (NMs) via standard toxicity tests does not cover many of the NMs specificities. One of the recommendations lays on understanding the mechanisms of action, as these can help predicting long-term effects and safe-by-design production. In the present study, we used the high-throughput gene expression tool, developed for Enchytraeus crypticus (4 × 44k Agilent microarray), to study the effects of exposure to several copper (Cu) forms. The Cu treatments included two NMs (spherical and wires) and two copper-salt treatments (CuNO₃ spiked and Cu salt field historical contamination). To relate gene expression with higher effect level, testing was done with reproduction effect concentrations (EC₂₀, EC₅₀), using 3 and 7 days as exposure periods. Results showed that time plays a major role in the transcriptomic response, most of it occurring after 3 days. Analysis of gene expression profiles showed that Cu-salt-aged and Cu-nanowires (Nwires) differed from CuNO₃ and Cu-nanoparticles (NPs). Functional analysis revealed specific mechanisms: Cu-NPs uniquely affected senescence and cuticle pattern formation, which can result from the contact of the NPs with the worms' tegument. Cu-Nwires affected reproduction via male gamete generation and hermaphrodite genitalia development. CuNO₃ affected neurotransmission and locomotory behavior, both of which can be related with avoidance response. Cu salt-aged uniquely affected phagocytosis and reproductive system development (via different mechanisms than Cu-Nwires). For the first time for Cu (nano)materials, the adverse outcome pathways (AOPs) drafted here provide an overview for common and unique effects per material and linkage with apical effects.

Comparison of alternative approaches for analysing multi-level RNA-seq data

RNA sequencing (RNA-seq) is widely used for RNA quantification in the environmental, biological and medical sciences. It enables the description of genome-wide patterns of expression and the identification of regulatory interactions and networks. The aim of RNA-seq data analyses is to achieve rigorous quantification of genes/transcripts to allow a reliable prediction of differential expression (DE), despite variation in levels of noise and inherent biases in sequencing data. This can be especially challenging for datasets in which gene expression differences are subtle, as in the behavioural transcriptomics test dataset from D. melanogaster that we used here. We investigated the power of existing approaches for quality checking mRNA-seq data and explored additional, quantitative quality checks. To accommodate nested, multi-level experimental designs, we incorporated sample layout into our analyses. We employed a subsampling without replacement-based normalization and an identification of DE that accounted for the hierarchy and amplitude of effect sizes within samples, then evaluated the resulting differential expression call in comparison to existing approaches. In a final step to test for broader applicability, we applied our approaches to a published set of H. sapiens mRNA-seq samples, The dataset-tailored methods improved sample comparability and delivered a robust prediction of subtle gene expression changes. The proposed approaches have the potential to improve key steps in the analysis of RNA-seq data by incorporating the structure and characteristics of biological experiments.