Diferentsiaalse geeniekspressiooni erinevuste hindamine mitmete indikaatorite alusel

Väitekirja elektrooniline versioon ei sisalda publikatsioone.Üksikud erandid välja arvatud, on genoom meie keha igas rakus täpselt ühesugune. Ometi koosneme paljudest erineva kuju, füsioloogia ja ülesandega rakkudest. Kirjeldatud variatsiooni aluseks on genoomis paiknevate geenide koordineeritud aktiivsus. Teisisõnu, igas rakus on oma programm, mille järgi reguleeritakse geenide aktiivsust, mis omakorda määrab raku morfoloogia ja funktsiooni. Geeni aktiivsust ehk geeni ekspressiooni on võimalik mõõta erinevate tehnoloogiate abil. Üheks levinumaks vahendiks on juba kaks aastakümmet tagasi välja arendatud DNA-mikrokiipide tehnoloogia, mis võimaldab korraga mõõta kümnete tuhandete geenide ekspressiooni. Mikrokiipide oluliseks eeliseks teiste alternatiivsete tehnoloogiate ees on aastate jooksul välja töötatud standardid andmete hoiustamiseks ja analüüsimiseks. Lisaks on mikrokiibiga mõõdetud geeni ekspressiooni andmete hulk avalikes andmebaasides suurem kui teiste tehnoloogiate puhul. Seega on mikrokiipide abil tehtud eksperimentide suur hulk heaks platvormiks olemasolevate andmete kasutamiseks uute hüpoteeside püstitamisel ja lisandväärtust loovate bioinformaatiliste tööriistade arendamisel. Samas eeldab see paindlikke lahendusi, mis aitavad võimalikult efektiivselt andmetes peituvat potentsiaali ära kasutada. Käesolev töö pakuv välja uudse diferentsiaalse ekspressiooni analüüsi meetodoloogia (Differential Expression from Multiple Indicators, DEMI) mikrokiibi abil tehtud eksperimendist saadud andmete analüüsimiseks. Antud metodoloogia loomise motivatsiooniks oli kasutada kõrgtihedusega mikrokiibi tehnoloogia korduvmõõtmistes (samaaegselt mõõdetakse ühte geeni mitmest erinevast kohast) leiduvat informatsiooni senisest suuremal määral, et suurendada meetodi tundlikust. Võrdlemisel teiste meetoditega leidsime, et DEMI sooritus on stabiilselt hea, sõltumata mikrokiibi platvormist ja replikaatide arvust. Biloogiliste replikaatide vähesus on tihti probleemiks näiteks kliiniliste proovide puhul, mille hankimine on keeruline või pilootkatsete tegemisel piiratud ressursside tingimuses. Lisaks võimaldab DEMI analüüsida erineva ülesehitusega geeni ekspressiooni eksperimente. Sealhulgas eksperimente, kus on vaja analüüsida ajast või doosist sõltuvat geeni ekspressioonidünaamikat olukorras, kus replikaadid puuduvad, või tuvastamaks genoomseid piirkondi, kus on toimunud kõrvutiasetsevate geenide aktiivsuse ühesuunaline ekspressiooni muutus (näiteks vähis esinevate epigeneetiliste mõjutuste toimel). Kokkuvõttes pakub DEMI paindliku lahenduse olemasolevate ja uute andmete analüüsimiseks ning võimaldab teadlastel küsida andmetelt veel esitamata küsimusi uuest vaatenurgast.  With very few exceptions the genome is identical in every cell of our body. Nevertheless, our body consists of many different cells with unique shape, physiology and behavior. This variation in cell types is achieved by coordinated activity of every gene in the genome. In other words, every cell has it’s own program that regulates the activity of the genes, which subsequently determines the cell’s morphology and functionality. There are several technologies that can be used for measuring the activity of a gene i.e. gene expression. One of the best-known and widely used technologies is DNA-microarray developed more than two decades ago. The advantage of microarrays is that they can measure gene expression of tens of thousands of genes simultaneously. Additionally, good standards for data housing and data analysis have been established and currently the amount of microarray data in public warehouses from experiments measuring gene expression is unmatched. Therefore the reuse of available data to find answers to alternative hypothesis and the development of added-value bioinformatics tools requires flexible solutions that best exploit the potential hidden in the data. This work focused on developing a new framework for differential expression analysis of microarray data, termed Differential Expression from Multiple Indicators (DEMI). Our motivation was to utilize the information stored in the repeated measurements on microarrays (a gene’s expression is measured from multiple locations) to increase the sensitivity of the analysis. In comparison to other well-established methods, DEMI demonstrated a good and stable performance regardless of the microarray platform and sample size. This is especially important when samples are hard to obtain, like in clinical trials, or due to limitation in the resource, which is often the case in pilot studies. Furthermore, DEMI can handle experiments with non-conventional design, like time- or dose-dependent differential expression analysis with no replicates and identify genomic regions with unidirectional changes in gene expression levels of neighboring genes (e.g. a decrease in gene expression levels of neighboring genes can result due to large-scale epigenetic changes caused by a cancer). All in all, DEMI provides a flexible solution for differential expression analysis and is able to answer new questions from already published data

Epidemiologically most successful SARS-CoV-2 variant: concurrent mutations in RNA-dependent RNA polymerase and spike protein

The D614G mutation of the Spike protein is thought to be relevant for SARS-CoV-2 infection. Here we report biological and epidemiological aspects of this mutation. Using pseudotyped lentivectors, we were able to confirm that the G614 variant of the Spike protein is markedly more infectious than the ancestral D614 variant. We demonstrate by molecular modelling that the replacement of aspartate by glycine in position 614 facilitates the transition towards an open state of the Spike protein. To understand whether the increased infectivity of the D614 variant explains its epidemiological success, we analysed the evolution of 27,086 high-quality SARS-CoV-2 genome sequences from GISAID. We observed striking coevolution of D614G with the P323L mutation in the viral polymerase. Importantly, exclusive presence of G614 or L323 did not become epidemiologically relevant. In contrast, the combination of the two mutations gave rise to a viral G/L variant that has all but replaced the initial D/P variant. There was no significant correlation between reported COVID mortality in different countries and the prevalence of the Wuhan versus G/L variant. However, when comparing the speed of emergence and the ultimate predominance in individual countries, the G/L variant displays major epidemiological supremacy. Our results suggest that the P323L mutation, located in the interface domain of the RNA-dependent RNA polymerase (RdRp), is a necessary alteration that led to the epidemiological success of the present variant of SARS-CoV-2

Markers of Murine Embryonic and Neural Stem Cells, Neurons and Astrocytes: Reference Points for Developmental Neurotoxicity Testing

Developmental neurotoxicity (DNT) is a serious concern for environmental chemicals, as well as for food and drug constituents. Animal-based DNT models have relatively low sensitivity, and they are limited by high work-load, cost and animal ethics. Murine embryonic stem cells (mESC) recapitulate several critical processes involved in the development of the nervous system if they are induced to differentiate into neural cells. They therefore represent an alternative toxicological model to predict human hazard. In this review, we discuss how mESC can be used for DNT assays. We have compiled a list of mRNA markers that define undifferentiated mESC (n = 42); neural stem cells (n = 73), astrocytes (n = 25) and the pattern of different neuronal and non-neuronal cell types generated (n = 57). We propose that transcriptional profiling can be used as a sensitive endpoint in toxicity assays to distinguish neural differentiation states during normal and disturbed development. Importantly, we believe that it can be scaled up to relatively high throughput whilst still providing rich information on disturbances affecting small cell subpopulations. Moreover, this approach can provide insight into underlying mechanisms and pathways of toxicity. We broadly discuss the methodological basis of marker lists and DNT assay design. The discussion is put in the context of a new generation of alternative assays (embryonic stem cell based DNT testing = ESDNT V2.0), that may later include human induced pluripotent stem cells, and that are not designed for 1:1 replacement of animal experiments, but are rather intended to improve human risk assessment by using independent scientific principles.JRC.I.2-Validation of Alternative Method

Correction: Melanocytes in the Skin - Comparative Whole Transcriptome Analysis of Main Skin Cell Types.

[This corrects the article DOI: 10.1371/journal.pone.0115717.]

Neuroglobin-deficiency exacerbates Hif1A and c-FOS response, but does not affect neuronal survival during severe hypoxia in vivo

Neuroglobin (Ngb), a neuron-specific globin that binds oxygen in vitro, has been proposed to play a key role in neuronal survival following hypoxic and ischemic insults in the brain. Here we address whether Ngb is required for neuronal survival following acute and prolonged hypoxia in mice genetically Ngb-deficient (Ngb-null). Further, to evaluate whether the lack of Ngb has an effect on hypoxia-dependent gene regulation, we performed a transcriptome-wide analysis of differential gene expression using Affymetrix Mouse Gene 1.0 ST arrays. Differential expression was estimated by a novel data analysis approach, which applies non-parametric statistical inference directly to probe level measurements.Ngb-null mice were born in expected ratios and were normal in overt appearance, home-cage behavior, reproduction and longevity. Ngb deficiency had no effect on the number of neurons, which stained positive for surrogate markers of endogenous Ngb-expressing neurons in the wild-type (wt) and Ngb-null mice after 48 hours hypoxia. However, an exacerbated hypoxia-dependent increase in the expression of c-FOS protein, an immediate early transcription factor reflecting neuronal activation, and increased expression of Hif1A mRNA were observed in Ngb-null mice. Large-scale gene expression analysis identified differential expression of the glycolytic pathway genes after acute hypoxia in Ngb-null mice, but not in the wts. Extensive hypoxia-dependent regulation of chromatin remodeling, mRNA processing and energy metabolism pathways was apparent in both genotypes.According to these results, it appears unlikely that the loss of Ngb affects neuronal viability during hypoxia in vivo. Instead, Ngb-deficiency appears to enhance the hypoxia-dependent response of Hif1A and c-FOS protein while also altering the transcriptional regulation of the glycolytic pathway. Bioinformatic analysis of differential gene expression yielded novel predictions suggesting that chromatin remodeling and mRNA metabolism are among the key regulatory mechanisms when adapting to prolonged hypoxia

Melanocytes in the Skin – Comparative Whole Transcriptome Analysis of Main Skin Cell Types

<div><p>Melanocytes possess several functions besides a role in pigment synthesis, but detailed characteristics of the cells are still unclear. We used whole transcriptome sequencing (RNA-Seq) to assess differential gene expression of cultivated normal human melanocytes with respect to keratinocytes, fibroblasts and whole skin. The present results reveal cultivated melanocytes as highly proliferative cells with possible stem cell-like properties. The enhanced readiness to regenerate makes melanocytes the most vulnerable cells in the skin and explains their high risk of developing into malignant melanoma.</p></div