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As the COVID-19 pandemic continues to affect the world, a new variant of concern, B.1.1.529 (Omicron), has been recently identified by the World Health Organization. At the time of writing, there are still no available primer sets specific to the Omicron variant, and its identification is only possible by using multiple targets, checking for specific failures, amplifying the suspect samples, and sequencing the results. This procedure is considerably time-consuming, in a situation where time might be of the essence. In this paper we use an Artificial Intelligence (AI) technique to identify a candidate primer set for the Omicron variant. The technique, based on Evolutionary Algorithms (EAs), has been already exploited in the recent past to develop primers for the B.1.1.7/Alpha variant, that have later been successfully tested in the lab. Starting from available virus samples, the technique explores the space of all possible subsequences of viral RNA, evaluating them as candidate primers. The criteria used to establish the suitability of a sequence as primer includes its frequency of appearance in samples labeled as Omicron, its absence from samples labeled as other variants, a specific range of melting temperature, and its CG content. The resulting primer set has been validated in silico and proves successful in preliminary laboratory tests. Thus, these results prove further that our technique could be established as a working template for a quick response to the appearance of new SARS-CoV-2 variants.

Background Type 2 diabetes (T2D) is associated with coronary microvascular dysfunction, which is thought to contribute to compromised diastolic function, ultimately culminating in heart failure with preserved ejection fraction (HFpEF). The molecular mechanisms remain incompletely understood, and no early diagnostics are available. We sought to gain insight into biomarkers and potential mechanisms of microvascular dysfunction in obese mouse (db/db) and lean rat (Goto-Kakizaki) pre-clinical models of T2D-associated diastolic dysfunction. Methods The microRNA (miRNA) content of circulating extracellular vesicles (EVs) was assessed in T2D models to identify biomarkers of coronary microvascular dysfunction/rarefaction. The potential source of circulating EV-encapsulated miRNAs was determined, and the mechanisms of induction and the function of candidate miRNAs were assessed in endothelial cells (ECs). Results We found an increase in miR-30d-5p and miR-30e-5p in circulating EVs that coincided with indices of coronary microvascular EC dysfunction (i.e., markers of oxidative stress, DNA damage/senescence) and rarefaction, and preceded echocardiographic evidence of diastolic dysfunction. These miRNAs may serve as biomarkers of coronary microvascular dysfunction as they are upregulated in ECs of the left ventricle of the heart, but not other organs, in db/db mice. Furthermore, the miR-30 family is secreted in EVs from senescent ECs in culture, and ECs with senescent-like characteristics are present in the db/db heart. Assessment of miR-30 target pathways revealed a network of genes involved in fatty acid biosynthesis and metabolism. Over-expression of miR-30e in cultured ECs increased fatty acid β-oxidation and the production of reactive oxygen species and lipid peroxidation, while inhibiting the miR-30 family decreased fatty acid β-oxidation. Additionally, miR-30e over-expression synergized with fatty acid exposure to down-regulate the expression of eNOS, a key regulator of microvascular and cardiomyocyte function. Finally, knock-down of the miR-30 family in db/db mice decreased markers of oxidative stress and DNA damage/senescence in the microvascular endothelium. Conclusions MiR-30d/e represent early biomarkers and potential therapeutic targets that are indicative of the development of diastolic dysfunction and may reflect altered EC fatty acid metabolism and microvascular dysfunction in the diabetic heart.

During development, cell identity is established reproducibly among individuals through the expression of specific genes at the correct time and correct location in space. How genes extract and combine both positional and temporal information from different transcription factor (TF) profiles along polarity axes remain largely unexplored. Here, we showcase the classic hunchback gene in fruit fly embryos, with focus on 3 of its main TFs: Bicoid, Zelda and Hunchback proteins. We constructed a series of synthetic MS2 reporters, where the numbers and combination of binding sites for each TF are varied. Using live imaging of transcription dynamics by these synthetic reporters and modeling tools, we show that i) a Bicoid-only synthetic reporter needs 3 more Bicoid binding sites than found in the hunchback promoter to recapitulates almost all spatial features of early hb expression but takes more time to reach steady state; ii) Hunchback and Zelda binding sites combined with Bicoid sites both reduce the time to reach steady state and increase expression at a different step in the activation process: Zld sites lower the Bicoid threshold required for activation while Hb sites increase the polymerase firing rate and reduce bursting; iii) the shift of the Bicoid-only reporter induced by a reduction by half of Bicoid concentrations indicates that the decay length of the Bicoid activity gradient is lower than the decay length of the Bicoid protein gradient. Altogether, this work indicates that Bicoid is the main source of positional information for hunchback expression and places back the Bicoid system within the physical limits of an equilibrium model.

Quantitative cell biology requires precise and accurate concentration measurements, resolved both in space and time. Fluorescence correlation spectroscopy (FCS) has been held as a promising technique to perform such measurements because the fluorescence fluctuations it relies on are directly dependent on the absolute number of fluorophores in the detection volume. However, the most interesting applications are in cells, where autofluorescence and confinement result in strong background noise and important levels of photobleaching. Both noise and photobleaching introduce systematic bias in FCS concentration measurements and need to be corrected for. Here, we propose to make use of the photobleaching inevitably occurring in confined environments to perform series of FCS measurements at different fluorophore concentration, which we show allows a precise in situ measurement of both background noise and molecular brightness. Such a measurement can then be used as a calibration to transform confocal intensity images into concentration maps. The power of this approach is first illustrated with in vitro measurements using different dye solutions, then its applicability for in vivo measurements is demonstrated in Drosophila embryos for a model nuclear protein and for two morphogens, Bicoid and Capicua.

As the COVID-19 pandemic continues, new SARS-CoV-2 variants with potentially dangerous features have been identified by the scientific community. Variant B.1.1.7 lineage clade GR from Global Initiative on Sharing All Influenza Data (GISAID) was first detected in the UK, and it appears to possess an increased transmissibility. At the same time, South African authorities reported variant B.1.351, that shares several mutations with B.1.1.7, and might also present high transmissibility. Earlier this year, a variant labelled P.1 with 17 non-synonymous mutations was detected in Brazil. Recently the World Health Organization has raised concern for the variants B.1.617.2 mainly detected in India but now exported worldwide. It is paramount to rapidly develop specific molecular tests to uniquely identify new variants. Using a completely automated pipeline built around deep learning and evolutionary algorithms techniques, we designed primer sets specific to variants B.1.1.7, B.1.351, P.1 and respectively. Starting from sequences openly available in the GISAID repository, our pipeline was able to deliver the primer sets for each variant. In-silico tests show that the sequences in the primer sets present high accuracy and are based on 2 mutations or more. In addition, we present an analysis of key mutations for SARS-CoV-2 variants. Finally, we tested the designed primers for B.1.1.7 using RT-PCR. The presented methodology can be exploited to swiftly obtain primer sets for each new variant, that can later be a part of a multiplexed approach for the initial diagnosis of COVID-19 patients.

The SARS-CoV-2 variant B.1.1.7 lineage, also known as clade GR from Global Initiative on Sharing All Influenza Data (GISAID), Nextstrain clade 20B, or Variant Under Investigation in December 2020 (VUI – 202012/01), appears to have an increased transmissability in comparison to other variants. Thus, to contain and study this variant of the SARS-CoV-2 virus, it is necessary to develop a specific molecular test to uniquely identify it. Using a completely automated pipeline involving deep learning techniques, we designed a primer set which is specific to SARS-CoV-2 variant B.1.1.7 with >99% accuracy, starting from 8,923 sequences from GISAID. The resulting primer set is in the region of the synonymous mutation C16176T in the ORF1ab gene, using the canonical sequence of the variant B.1.1.7 as a reference. Furtherin-silicotesting shows that the primer set’s sequences do not appear in different viruses, using 20,571 virus samples from the National Center for Biotechnology Information (NCBI), nor in other coronaviruses, using 487 samples from National Genomics Data Center (NGDC). In conclusion, the presented primer set can be exploited as part of a multiplexed approach in the initial diagnosis of Covid-19 patients, or used as a second step of diagnosis in cases already positive to Covid-19, to identify individuals carrying the B.1.1.7 variant.

Telomeres are maintained in a heterochromatic state that represses transcription of subtelomeric genes, a phenomenon known as telomere position effect. Nevertheless, telomeric DNA is actively transcribed, leading to the synthesis of telomeric repeat-containing noncoding RNA or TERRA. This nuclear noncoding RNA has been proposed to play important roles at telomeres, regulating their silencing, capping, repair and elongation by telomerase. In the budding yeast Saccharomyces cerevisiae, TERRA accumulation is repressed by telomeric silencing and the Rat1 exonuclease. On the other hand, telomere shortening promotes expression of TERRA. So far, little is known about the biological processes that induce TERRA expression in yeast. Understanding the dynamics of TERRA expression and localization is essential to define its function in telomere biology. Here, we aim to study the dynamics of TERRA expression during yeast cell growth. Using live-cell imaging, RNA-FISH and quantitative RT-PCR, we show that TERRA expression is induced as yeast cells undergo diauxic shift, a lag phase during which yeast cells switch their metabolism from anaerobic fermentation to oxidative respiration. This induction is transient as TERRA levels decrease during post-diauxic shift. The increased expression of TERRA is not due to the shortening of telomeres or increased stability of this transcript. Surprisingly, this induction is coincident with a cytoplasmic accumulation of TERRA molecules. Our results suggest that TERRA transcripts may play extranuclear functions with important implications in telomere biology and add a novel layer of complexity in the interplay between telomere biology, metabolism and stress response.

We present the LiveFly toolbox for quantitative analysis of transcription dynamics in live Drosophila embryos. The toolbox allows users to process two-color 3D confocal movies acquired using nuclei-labeling and the fluorescent RNA-tagging system described in the previous chapter and export the nuclei's position as a function of time, their lineages and the intensity traces of the active loci. The toolbox, which is tailored for the context of Drosophila early development, is semiautomatic, and requires minimal user intervention. It also includes a tool to combine data from multiple movies and visualize several features of the intensity traces and the expression pattern.

Live imaging has been used in recent years for the understanding of dynamic processes in biology, such as embryo development. This was made possible by a combination of advancements in microscopy, leading to improved signal-to-noise ratios and better spatial and temporal resolutions, and by the development of new fluorescence markers, allowing for the quantification of protein expression and transcriptional dynamics in vivo. Here we describe a general protocol, which can be used in standard confocal microscopes to image early Drosophila melanogaster embryos, in order to learn about the transcriptional dynamics of a fluorescently labeled RNA.

Fly development amazes us by the precision and reproducibility of gene expression, especially since the initial expression patterns are established during very short nuclear cycles. Recent live imaging of hunchback promoter dynamics shows a stable steep binary expression pattern established within the three minute interphase of nuclear cycle 11. Considering expression models of different complexity, we explore the trade-off between the ability of a regulatory system to produce a steep boundary and minimize expression variability between different nuclei. We show how a limited readout time imposed by short developmental cycles affects the gene’s ability to read positional information along the embryo’s anterior posterior axis and express reliably. Comparing our theoretical results to real-time monitoring of the hunchback transcription dynamics in live flies, we discuss possible regulatory strategies, suggesting an important role for additional binding sites, gradients or non-equilibrium binding and modified transcription factor search strategies., Author summary Despite very limited time, organisms develop in reproducible ways. In the early stages of fly development the information about maternal signals is read out in a few minutes to produce steep and precise gene expression patterns. Motivated by recent live imaging experiments in fly embryos, we explore the consequences of the trade-off between a rushed but reproducible readout and a steep expression pattern on the regulatory modules of gene expression. We show that the current view of one anterior gradient morphogen binding to six binding sites is quantitatively inconsistent with the experimental data given the short readout time, suggesting other regulatory features.

Morphogen gradients provide concentration-dependent positional information along polarity axes. Although the dynamics of the establishment of these gradients is well described, precision and noise in the downstream activation processes remain elusive. A simple paradigm to address these questions is the Bicoid morphogen gradient that elicits a rapid step-like transcriptional response in young fruit fly embryos. Focusing on the expression of the major Bicoid target, hunchback (hb), at the onset of zygotic transcription, we used the MS2-MCP approach which combines fluorescent labeling of nascent mRNA with live imaging at high spatial and temporal resolution. Removing 36 putative Zelda binding sites unexpectedly present in the original MS2 reporter, we show that the 750 bp of the hb promoter are sufficient to recapitulate endogenous expression at the onset of zygotic transcription. After each mitosis, in the anterior, expression is turned on to rapidly reach a plateau with all nuclei expressing the reporter. Consistent with a Bicoid dose-dependent activation process, the time period required to reach the plateau increases with the distance to the anterior pole. Despite the challenge imposed by frequent mitoses and high nuclei-to-nuclei variability in transcription kinetics, it only takes 3 minutes at each interphase for the MS2 reporter loci to distinguish subtle differences in Bicoid concentration and establish a steadily positioned and steep (Hill coefficient ~ 7) expression boundary. Modeling based on the cooperativity between the 6 known Bicoid binding sites in the hb promoter region, assuming rate limiting concentrations of the Bicoid transcription factor at the boundary, is able to capture the observed dynamics of pattern establishment but not the steepness of the boundary. This suggests that a simple model based only on the cooperative binding of Bicoid is not sufficient to describe the spatiotemporal dynamics of early hb expression., Author summary During development, the first thing that an embryo needs to know is the orientation of its body. We study how the head-to-tail axis forms in the fruit fly embryo. To position the axis, the embryo relies on proteins called morphogens broadcasting instructions to other genes, so that cells know, depending on where they are along the axis, what they should become. The concentration of the Bicoid morphogen is much higher in the head of the embryo and lower towards the tail. Bicoid activates hunchback, which divides the embryo in two parts. By visualizing this process in real time in living embryos, we see the hunchback gene activated very efficiently in the head part, where each nucleus expresses the gene, whereas it is not expressed at all in the tail part. Intriguingly, the boundary separating the two domains is precisely positioned and becomes very steep in no more than three minutes. We use a modeling approach to understand how this is achieved so rapidly. Given the parameters of the system, we find that although our model is able to reproduce the fast dynamics of the process, it fails to reproduce the steepness of the boundary suggesting that a more complex approach is needed to capture the additional mechanisms involved.

Live imaging has been used in recent years for the understanding of dynamic processes in biology, such as embryo development. This was made possible by a combination of advancements in microscopy, leading to improved signal-to-noise ratios and better spatial and temporal resolutions, and by the development of new fluorescence markers, allowing for the quantification of protein expression and transcriptional dynamics in vivo. Here we describe a general protocol, which can be used in standard confocal microscopes to image early Drosophila melanogaster embryos, in order to learn about the transcriptional dynamics of a fluorescently labeled RNA.

We present the LiveFly toolbox for quantitative analysis of transcription dynamics in live Drosophila embryos. The toolbox allows users to process two-color 3D confocal movies acquired using nuclei-labeling and the fluorescent RNA-tagging system described in the previous chapter and export the nuclei's position as a function of time, their lineages and the intensity traces of the active loci. The toolbox, which is tailored for the context of Drosophila early development, is semiautomatic, and requires minimal user intervention. It also includes a tool to combine data from multiple movies and visualize several features of the intensity traces and the expression pattern.

The simultaneous expression of the hunchback gene in the numerous nuclei of the developing fly embryo gives us a unique opportunity to study how transcription is regulated in living organisms. A recently developed MS2-MCP technique for imaging nascent messenger RNA in living Drosophila embryos allows us to quantify the dynamics of the developmental transcription process. The initial measurement of the morphogens by the hunchback promoter takes place during very short cell cycles, not only giving each nucleus little time for a precise readout, but also resulting in short time traces of transcription. Additionally, the relationship between the measured signal and the promoter state depends on the molecular design of the reporting probe. We develop an analysis approach based on tailor made autocorrelation functions that overcomes the short trace problems and quantifies the dynamics of transcription initiation. Based on live imaging data, we identify signatures of bursty transcription initiation from the hunchback promoter. We show that the precision of the expression of the hunchback gene to measure its position along the anterior-posterior axis is low both at the boundary and in the anterior even at cycle 13, suggesting additional post-transcriptional averaging mechanisms to provide the precision observed in fixed embryos., Author Summary The fly embryo provides a natural laboratory to study the dynamics of transcription and its implications for the developing organism. Using live imaging experiments we investigate the nature of transcription regulation of the hunchback gene—the first to read out the maternal Bicoid gradient. While traditional time trace analysis methods based on OFF time distributions or autocorrelation functions fail for short signals, our tailored autocorrelation function overcomes these limitations revealing bursty dynamics that is reproducible between cell cycles and embryos. The inferred rates result in a lot of variability in the readout of nuclei sensing similar Bicoid concentrations, suggesting additional readout mechanisms than a one-to-one mapping of the input onto the output.

Elongation of a short telomere depends on the action of multiple telomerase molecules, which are visible as telomerase RNA foci or clusters associated with telomeres in yeast and mammalian cells. How several telomerase molecules act on a single short telomere is unknown. Herein, we report that the telomeric noncoding RNA TERRA is involved in the nucleation of telomerase molecules into clusters prior to their recruitment at a short telomere. We find that telomere shortening induces TERRA expression, leading to the accumulation of TERRA molecules into a nuclear focus. Simultaneous time-lapse imaging of telomerase RNA and TERRA reveals spontaneous events of telomerase nucleation on TERRA foci in early S phase, generating TERRA-telomerase clusters. This cluster is subsequently recruited to the short telomere from which TERRA transcripts originate during S phase. We propose that telomere shortening induces noncoding RNA expression to coordinate the recruitment and activity of telomerase molecules at short telomeres.