Antibody-assisted selective isolation of Purkinje cell nuclei from mouse cerebellar tissue.

We developed a method that utilizes fluorescent labeling of nuclear envelopes alongside cytometry sorting for the selective isolation of Purkinje cell (PC) nuclei. Beginning with SUN1 reporter mice, we GFP-tagged envelopes to confirm that PC nuclei could be accurately separated from other cell types. We then developed an antibody-based protocol to make PC nuclear isolation more robust and adaptable to cerebellar tissues of any genotypic background. Immunofluorescent labeling of the nuclear membrane protein RanBP2 enabled the isolation of PC nuclei from C57BL/6 cerebellum. By analyzing the expression of PC markers, nuclear size, and nucleoli number, we confirmed that our method delivers a pure fraction of PC nuclei. To demonstrate its applicability, we isolated PC nuclei from spinocerebellar ataxia type 7 (SCA7) mice and identified transcriptional changes in known and new disease-associated genes. Access to pure PC nuclei offers insights into PC biology and pathology, including the nature of selective neuronal vulnerability.

Targeting sgRNA N secondary structure as a way of inhibiting SARS-CoV-2 replication.

SARS-CoV-2 is a betacoronavirus that causes COVID-19, a global pandemic that has resulted in many infections, deaths, and socio-economic challenges. The virus has a large positive-sense, single-stranded RNA genome of ∼30 kb, which produces subgenomic RNAs (sgRNAs) through discontinuous transcription. The most abundant sgRNA is sgRNA N, which encodes the nucleocapsid (N) protein. In this study, we probed the secondary structure of sgRNA N and a shorter model without a 3' UTR in vitro, using the SHAPE (selective 2'-hydroxyl acylation analyzed by a primer extension) method and chemical mapping with dimethyl sulfate and 1-cyclohexyl-(2-morpholinoethyl) carbodiimide metho-p-toluene sulfonate. We revealed the secondary structure of sgRNA N and its shorter variant for the first time and compared them with the genomic RNA N structure. Based on the structural information, we designed gapmers, siRNAs and antisense oligonucleotides (ASOs) to target the N protein coding region of sgRNA N. We also generated eukaryotic expression vectors containing the complete sequence of sgRNA N and used them to screen for new SARS-CoV-2 gene N expression inhibitors. Our study provides novel insights into the structure and function of sgRNA N and potential therapeutic tools against SARS-CoV-2.

Alterations in N-glycosylation of HCV E2 Protein in Children Patients with IFN-RBV Therapy Failure.

The glycosylation of viral envelope proteins plays an important role in virus biology and the immune response of the host to infection. Hepatitis C virus (HCV) envelope proteins E1 and E2, key players in virus entry and spread, are highly N-glycosylated and possess 4 (5 in certain genotypes) to 11 conserved glycosylation sites, respectively. Many published results based on recombinant proteins indicate that the glycan shield can mask the epitopes targeted by neutralizing antibodies. Glycan shifting within the conserved linear E2 region (412-423) could be one of the escape strategies used by HCV. In the present report, we isolated E2 genes from samples (collected before the IFN-RBV therapy) originating from pediatric patients infected with HCV gt 1a. We analyzed the biochemical properties of cloned E2 glycoprotein variants and investigated their glycosylation status. The sequencing of E2 genes isolated from patients who did not respond to therapy revealed mutations at N-glycosylation sites, thus leading to a lower molecular weight and a low affinity to both linear and conformational neutralizing antibodies. The loss of the glycosylation site within the conserved epitope (amino acid 417) impaired the binding with AP33, an antibody that potently neutralizes all genotypes of HCV. Our findings, based on clinical samples, confirm the influence of N-glycosylation aberrations on the antigenic and conformational properties of HCV E1/E2, which may possibly correlate with the outcome of therapy in patients.

Engineered deaminases as a key component of DNA and RNA editing tools.

Over recent years, zinc-dependent deaminases have attracted increasing interest as key components of nucleic acid editing tools that can generate point mutations at specific sites in either DNA or RNA by combining a targeting module (such as a catalytically impaired CRISPR-Cas component) and an effector module (most often a deaminase). Deaminase-based molecular tools are already being utilized in a wide spectrum of therapeutic and research applications; however, their medical and biotechnological potential seems to be much greater. Recent reports indicate that the further development of nucleic acid editing systems depends largely on our ability to engineer the substrate specificity and catalytic activity of the editors themselves. In this review, we summarize the current trends and achievements in deaminase engineering. The presented data indicate that the potential of these enzymes has not yet been fully revealed or understood. Several examples show that even relatively minor changes in the structure of deaminases can give them completely new and unique properties.

How to explore what is hidden? A review of techniques for vascular tissue expression profile analysis.

The evolution of plants to efficiently transport water and assimilates over long distances is a major evolutionary success that facilitated their growth and colonization of land. Vascular tissues, namely xylem and phloem, are characterized by high specialization, cell heterogeneity, and diverse cell components. During differentiation and maturation, these tissues undergo an irreversible sequence of events, leading to complete protoplast degradation in xylem or partial degradation in phloem, enabling their undisturbed conductive function. Due to the unique nature of vascular tissue, and the poorly understood processes involved in xylem and phloem development, studying the molecular basis of tissue differentiation is challenging. In this review, we focus on methods crucial for gene expression research in conductive tissues, emphasizing the importance of initial anatomical analysis and appropriate material selection. We trace the expansion of molecular techniques in vascular gene expression studies and discuss the application of single-cell RNA sequencing, a high-throughput technique that has revolutionized transcriptomic analysis. We explore how single-cell RNA sequencing will enhance our knowledge of gene expression in conductive tissues.

Dimensionality reduction by UMAP for visualizing and aiding in classification of imaging flow cytometry data.

Recent advances in imaging flow cytometry (IFC) have revolutionized high-throughput multiparameter analyses at single-cell resolution. Although enabling the discovery of population heterogeneities and the detection of rare events, IFC generates hyperdimensional datasets that demand innovative analytical approaches. Current methods work in a supervised manner, utilize only limited information content, or require large annotated reference datasets. Dimensionality reduction algorithms, including uniform manifold approximation and projection (UMAP), have been successfully applied to analyze the large number of parameters generated in various high-throughput techniques. Here, we apply a workflow incorporating UMAP to analyze different IFC datasets. We demonstrate that it out-competes other popular dimensionality reduction methods in speed and accuracy. Moreover, it enables fast visualization, clustering, and tagging of unannotated objects in large-scale experiments. We anticipate that our workflow will be a robust method to address complex IFC datasets, either alone or as an upstream addition to the deep learning approaches.

Molecular Composition of Serum Exosomes Could Discriminate Rectal Cancer Patients with Different Responses to Neoadjuvant Radiotherapy.

Identification of biomarkers that could be used for the prediction of the response to neoadjuvant radiotherapy (neo-RT) in locally advanced rectal cancer remains a challenge addressed by different experimental approaches. Exosomes and other classes of extracellular vesicles circulating in patients' blood represent a novel type of liquid biopsy and a source of cancer biomarkers. Here, we used a combined proteomic and metabolomic approach based on mass spectrometry techniques for studying the molecular components of exosomes isolated from the serum of rectal cancer patients with different responses to neo-RT. This allowed revealing several proteins and metabolites associated with common pathways relevant for the response of rectal cancer patients to neo-RT, including immune system response, complement activation cascade, platelet functions, metabolism of lipids, metabolism of glucose, and cancer-related signaling pathways. Moreover, the composition of serum-derived exosomes and a whole serum was analyzed in parallel to compare the biomarker potential of both specimens. Among proteins that the most properly discriminated good and poor responders were GPLD1 (AUC = 0.85, accuracy of 74%) identified in plasma as well as C8G (AUC = 0.91, accuracy 81%), SERPINF2 (AUC = 0.91, accuracy 79%) and CFHR3 (AUC = 0.90, accuracy 81%) identified in exosomes. We found that the proteome component of serum-derived exosomes has the highest capacity to discriminate samples of patients with different responses to neo-RT when compared to the whole plasma proteome and metabolome. We concluded that the molecular components of exosomes are associated with the response of rectal cancer patients to neo-RT and could be used for the prediction of such response.

At-C-RNA database, a one-stop source for information on circRNAs in Arabidopsis thaliana in a unified format.

Circular RNAs (circRNAs) are a large class of noncoding RNAs with functions that, in most cases, remain unknown. Recent genome-wide analysis of circRNAs using RNA-Seq has revealed that circRNAs are abundant and some of them conserved in plants. Furthermore, it has been shown that the expression of circRNAs in plants is regulated in a tissue-specific manner. Arabidopsis thaliana circular RNA database is a new resource designed to integrate and standardize the data available for circRNAs in a model plant A. thaliana, which is currently the best-characterized plant in terms of circRNAs. The resource integrates all applicable publicly available RNA-seq datasets. These datasets were subjected to extensive reanalysis and curation, yielding results in a unified format. Moreover, all data were normalized according to our optimized approach developed for circRNA identification in plants. As a result, the database accommodates circRNAs identified across organs and seedlings of wild-type A. thaliana and its single-gene knockout mutants for genes related to splicing. The database provides free access to unified data and search functionalities, thus enabling comparative analyses of A. thaliana circRNAs between organs, variants and studies for the first time. Database URLhttps://plantcircrna.ibch.poznan.pl/.

Expression Landscape of circRNAs in Arabidopsis thaliana Seedlings and Adult Tissues.

RNA-seq is currently the only method that can provide a comprehensive landscape of circular RNA (circRNAs) in the whole organism and its particular organs. Recent years have brought an increasing number of RNA-seq-based reports on plant circRNAs. Notably, the picture they revealed is questionable and depends on the applied circRNA identification and quantification techniques. In consequence, little is known about the biogenesis and functions of circRNAs in plants. In this work, we tested two experimental and six bioinformatics procedures of circRNA analysis to determine the optimal approach for studying the profiles of circRNAs in Arabidopsis thaliana. Then using the optimized strategy, we determined the accumulation of circular and corresponding linear transcripts in plant seedlings and organs. We observed that only a small fraction of circRNAs was reproducibly generated. Among them, two groups of circRNAs were discovered: ubiquitous and organ-specific. The highest number of circRNAs with significantly increased accumulation in comparison to other organs/seedlings was found in roots. The circRNAs in seedlings, leaves and flowers originated mainly from genes involved in photosynthesis and the response to stimulus. The levels of circular and linear transcripts were not correlated. Although RNase R treatment enriches the analyzed RNA samples in circular transcripts, it may also have a negative impact on the stability of some of the circRNAs. We also showed that the normalization of NGS data by the library size is not proper for circRNAs quantification. Alternatively, we proposed four other normalization types whose accuracy was confirmed by ddPCR. Moreover, we provided a comprehensive characterization of circRNAs in A. thaliana organs and in seedlings. Our analyses revealed that plant circRNAs are formed in both stochastic and controlled processes. The latter are less frequent and likely engage circRNA-specific mechanisms. Only a few circRNAs were organ-specific. The lack of correlation between the accumulation of linear and circular transcripts indicated that their biogenesis depends on different mechanisms.

Arabidopsis thaliana cbp80, c2h2, and flk Knockout Mutants Accumulate Increased Amounts of Circular RNAs.

Circular RNAs (circRNAs) are the products of the non-canonical splicing of pre-mRNAs. In contrast to humans and animals, our knowledge of the biogenesis and function of circRNAs in plants is very scarce. To identify proteins involved in plant circRNA generation, we characterized the transcriptomes of 18 Arabidopsis thaliana knockout mutants for genes related to splicing. The vast majority (>90%) of circRNAs were formed in more than one variant; only a small fraction of circRNAs was mutant-specific. Five times more circRNA types were identified in cbp80 and three times more in c2h2 mutants than in the wild-type. We also discovered that in cbp80, c2h2 and flk mutants, the accumulation of circRNAs was significantly increased. The increased accumulation of circular transcripts was not accompanied by corresponding changes in the accumulation of linear transcripts. Our results indicate that one of the roles of CBP80, C2H2 and FLK in splicing is to ensure the proper order of the exons. In the absence of one of the above-mentioned factors, the process might be altered, leading to the production of circular transcripts. This suggests that the transition toward circRNA production can be triggered by factors sequestering these proteins. Consequently, the expression of linear transcripts might be regulated through circRNA production.

Functional characterization of RNA fragments using high-throughput interactome screening.

Populations of small eukaryotic RNAs, in addition to relatively well recognized molecules such as miRNAs or siRNAs, also contain fragments derived from all classes of constitutively expressed non-coding RNAs. It has been recently demonstrated that the formation and accumulation of RNA fragments (RFs) is cell-/tissue-specific and depends on internal and external stimuli. Unfortunately, the mechanisms underlying RF biogenesis and function remain unclear. To better understand them, we employed RNA pull-down and mass spectrometry methods to characterize the interactions of seven RFs originating from tRNA, snoRNA and snRNA. By integrating our results with publicly available data on physical protein-protein interactions, we constructed an RF interactome network. We determined that the RF interactome comprises proteins generally different from those that interact with their parental full length RNAs. Proteins captured by the RFs were involved in mRNA splicing, tRNA processing, DNA recombination/replication, protein biosynthesis and carboxylic acid metabolism. Our data suggest that RFs can be endogenous aptamer-like molecules and potential players in recently revealed RNA-protein regulatory networks. SIGNIFICANCE: In the recent decade it has become evident that RNAs with well-known functions (for example tRNA, snoRNA or rRNA) can be cleaved to yield short fragments, whose role in cells remains only partially characterized. At the same time, unconventional interactions between mRNA and proteins without RNA-binding domains have been demonstrated, revealing novel layers of possible RNA-mediated regulation. Considering the above, we hypothesized that RNA fragments (RFs) can be endogenous aptamer-like molecules that unconventionally interact with proteins. In this study we identified protein partners of seven selected RFs. We found that RFs bind different set of proteins than their parental full length RNAs and identified proteins differentially bound by the particular RFs. These observations suggest biological relevance of the discovered interactions. Our data provide a novel perspective on the significance of RFs and point to this pool of molecules as to a rich collection of potential components of the recently discovered RNA-protein regulatory networks.

Effects of G-quadruplex topology on translational inhibition by tRNA fragments in mammalian and plant systems in vitro.

The folding of tRNA fragments (tRFs) into G-quadruplex structures and the implications of G-quadruplexes in translational inhibition have been studied mainly in mammalian systems. To increase our knowledge of these phenomena, we determined the influence of human and plant tRFs and model G-quadruplexes on translation in rabbit reticulocyte lysate and wheat germ extract. The efficiency of translational inhibition in the mammalian system was strongly associated with the type of G-quadruplex topology. In the plant system, the ability of a small RNA to adopt the G-quadruplex conformation was not sufficient to repress translation, indicating the importance of other structural determinants.

Small RNA fragments derived from multiple RNA classes - the missing element of multi-omics characteristics of the hepatitis C virus cell culture model.

BACKGROUND: A pool of small RNA fragments (RFs) derived from diverse cellular RNAs has recently emerged as a rich source of functionally relevant molecules. Although their formation and accumulation has been connected to various stress conditions, the knowledge on RFs produced upon viral infections is very limited. Here, we applied the next generation sequencing (NGS) to characterize RFs generated in the hepatitis C virus (HCV) cell culture model (HCV-permissive Huh-7.5 cell line). RESULTS: We found that both infected and non-infected cells contained a wide spectrum of RFs derived from virtually all RNA classes. A significant fraction of identified RFs accumulated to similar levels as miRNAs. Our analysis, focused on RFs originating from constitutively expressed non-coding RNAs, revealed three major patterns of parental RNA cleavage. We found that HCV infection induced significant changes in the accumulation of low copy number RFs, while subtly altered the levels of high copy number ones. Finally, the candidate RFs potentially relevant for host-virus interactions were identified. CONCLUSIONS: Our results indicate that RFs should be considered an important component of the Huh-7.5 transcriptome and suggest that the main factors influencing the RF biogenesis are the RNA structure and RNA protection by interacting proteins. The data presented here significantly complement the existing transcriptomic, miRnomic, proteomic and metabolomic characteristics of the HCV cell culture model.

Mutations in human AID differentially affect its ability to deaminate cytidine and 5-methylcytidine in ssDNA substrates in vitro.

Activation-induced cytidine deaminase (AID) is known for its established role in antibody production. AID induces the diversification of antibodies by deaminating deoxycytidine (C) within immunoglobulin genes. The capacity of AID to deaminate 5-methyldeoxycytidine (5 mC) and/or 5-hydroxymethyldeoxycytidine (5 hmC), and consequently AID involvement in active DNA demethylation, is not fully resolved. For instance, structural determinants of AID activity on different substrates remain to be identified. To better understand the latter issue, we tested how mutations in human AID (hAID) influence its ability to deaminate C, 5 mC, and 5 hmC in vitro. We showed that each of the selected mutations differentially affects hAID's ability to deaminate C and 5 mC. At the same time, we did not observe hAID activity on 5 hmC. Surprisingly, we found that the N51A hAID mutant, with no detectable activity on C, efficiently deaminated 5 mC, which may suggest different requirements for C and 5 mC deamination. Homology modeling and molecular dynamics simulations revealed that the pattern of enzyme-substrate recognition is one of the important factors determining enzyme activity on C and 5 mC. Consequently, we have proposed mechanisms that explain why wild type hAID more efficiently deaminates C than 5 mC in vitro and why 5 hmC is not deaminated.

Computational prediction of non-enzymatic RNA degradation patterns.

Since the beginning of the 21st century, an increasing interest in the research of ribonucleic acids has been observed in response to a surprising discovery of the role that RNA molecules play in the biological systems. It was demonstrated that they do not only take part in the protein synthesis (mRNA, rRNA, tRNA) but also are involved in the regulation of gene expression. Several classes of small regulatory RNAs have been discovered (e.g. microRNA, small interfering RNA, piwiRNA). Most of them are excised from specific double-stranded RNA precursors by enzymes that belong to the RNaseIII family (Drosha, Dicer or Dicer-like proteins). More recently, it has been shown that small regulatory RNAs are also generated as stable intermediates of RNA degradation (the so called RNA fragments originating from tRNA, snRNA, snoRNA etc.). Unfortunately, the mechanisms underlying biogenesis of the RNA fragments remain unclear. It is thought that several factors may be involved in the formation of the RNA fragments. The most important are the specific RNases, RNA-protein interactions and RNA structure. In this work, we focus on the RNA primary and secondary structures as factors influencing the RNA stability and consequently the pattern of RNA fragmentation. Earlier, we identified the major structural factors affecting non-enzymatic RNA degradation. Now, based on these data, we developed a new branch-and-cut algorithm that is able to predict the products of large RNA molecules' hydrolysis in vitro. We also present the experimental data that verify the results generated using this algorithm.

RNA-Seq-based analysis of differential gene expression associated with hepatitis C virus infection in a cell culture.

Hepatitis C virus (HCV) infection is one of the major causes of chronic liver diseases. Unfortunately, the mechanisms of HCV infection-induced liver injury and host-virus interactions are still not well recognized. To better understand these processes we determined the changes in the host gene expression that occur during HCV infection of Huh-7.5 cells. As a result, we identified genes that may contribute to the immune and metabolic cellular responses to infection. Pathway enrichment analysis indicated that HCV induced an increased expression of genes involved in mitogen-activated protein kinases signaling, adipocytokine signaling, cell cycle and nitrogen metabolism. In addition, the enrichment analyses of processes and molecular functions revealed that the up-regulated genes were mainly implicated in the negative regulation of phosphorylation. Construction of the pathway-gene-process network enabled exploration of a much more complex landscape of molecular interactions. Consequently, several essential processes altered by HCV infection were identified: negative regulation of cell cycle, response to endoplasmic reticulum stress, response to reactive oxygen species, toll-like receptor signaling and pattern recognition receptor signaling. The analyses of genes whose expression was decreased upon HCV infection showed that the latter were engaged in the metabolism of lipids and amino acids. Moreover, we observed disturbance in the cellular antiviral defense. Altogether, our results demonstrated that HCV infection elicits host response that includes a very wide range of cellular mechanisms. Our findings significantly broaden the understanding of complex processes that accompany HCV infection. Consequently, they may be used for developing new host-oriented therapeutic strategies.

Copy number variation of genes involved in the hepatitis C virus-human interactome.

Copy number variation (CNV) is a newly discovered form of intra-species genetic polymorphism that is defined as deletions or duplications of genome segments ranging from 1 kbp to several Mbp. CNV accounts for the majority of the genetic variation observed in humans (CNV regions cover more than 10% of the human genome); therefore, it may significantly influence both the phenotype and susceptibility to various diseases. Unfortunately, the impact of CNV on a number of diseases, including hepatitis C virus (HCV) infection, remains largely unexplored. Here, we analyzed 421 human genes encoding proteins that have been shown to interact with HCV proteins or genomic RNA (proteins from the HCV-human interactome). We found that 19 of the 421 candidate genes are located in putative CNV regions. For all of these genes, copy numbers were determined for European, Asiatic and African populations using the multiplex ligation-dependent amplification (MLPA) method. As a result, we identified 4 genes, IGLL1, MLLT4, PDPK1, PPP1R13L, for which the CN-genotype ranged from 1 to 6. All of these genes are involved in host-virus interaction; thus, their polymorphism has a potential impact on the development of HCV infection and/or therapy outcome.

Phylogeny and molecular evolution of the hepatitis C virus.

The hepatitis C virus (HCV) is a globally prevalent human pathogen that causes persistent liver infections in most infected individuals. HCV is classified into seven phylogenetically distinct genotypes, which have different geographical distributions and levels of genetic diversity. Some of these genotypes are endemic and highly divergent, whereas others disseminate rapidly on an epidemic scale but display lower variability. HCV phylogeny has an important impact on disease epidemiology and clinical practice because the viral genotype may determine the pathogenesis and severity of the resultant chronic liver disease. In addition, there is a clear association between the HCV genotype and its susceptibility to antiviral treatment. Similarly to other RNA viruses, in a single host, HCV exists as a combination of related but genetically different variants. The whole formation is the actual target of selection exerted by a host organism and antiviral therapeutics. The genetic structure of the viral population is largely shaped by mutations that are constantly introduced during an error-prone replication. However, it appears that genetic recombination may also contribute to this process. This heterogeneous collection of variants has a significant ability to evolve towards the fitness optimum. Interestingly, negative selection, which restricts diversity, emerges as an essential force that drives HCV evolution. It is becoming clear that HCV evolves to become stably adapted to the host environment. In this article we review the HCV phylogeny and molecular evolution in the context of host-virus interactions.

Multi-agent model of hepatitis C virus infection.

OBJECTIVES: The objective of this study is to design a method for modeling hepatitis C virus (HCV) infection using multi-agent simulation and to verify it in practice. METHODS AND MATERIALS: In this paper, first, the modeling of HCV infection using a multi-agent system is compared with the most commonly used model type, which is based on differential equations. Then, the implementation and results of the model using a multi-agent simulation is presented. To find the values of the parameters used in the model, a method using inverted simulation flow and genetic algorithm is proposed. All of the data regarding HCV infection are taken from the paper describing the model based on the differential equation to which the proposed method is compared. RESULTS: Important advantages of the proposed method are noted and demonstrated: these include flexibility, clarity, re-usability and the possibility to model more complex dependencies. Then, the simulation framework that uses the proposed approach is successfully implemented in C++ and is verified by comparing it to the approach based on differential equations. The verification proves that an objective function that performs the best is the function that minimizes the maximal differences in the data. Finally, an analysis of one of the already known models is performed, and it is proved that it incorrectly models a decay in the hepatocytes number by 40%. CONCLUSIONS: The proposed method has many advantages in comparison to the currently used model types and can be used successfully for analyzing HCV infection. With almost no modifications, it can also be used for other types of viral infections.

Identification of stable, high copy number, medium-sized RNA degradation intermediates that accumulate in plants under non-stress conditions.

It is becoming increasingly evident that the RNA degradome is a crucial component of the total cellular RNA pool. Here, we present an analysis of the medium-sized RNAs (midi RNAs) that form in Arabidopsis thaliana. Our analyses revealed that the midi RNA fraction contained mostly 20-70-nt-long fragments derived from various RNA species, including tRNA, rRNA, mRNA and snRNA. The majority of these fragments could be classified as stable RNA degradation intermediates (RNA degradants). Using two dimensional polyacrylamide gel electrophoresis, we demonstrated that high copy number RNA (hcn RNA) degradants appear in plant cells not only during stress, as it was earlier suggested. They are continuously produced also under physiological conditions. The data collected indicated that the accumulation pattern of the hcn RNA degradants is organ-specific and can be affected by various endogenous and exogenous factors. In addition, we demonstrated that selected degradants efficiently inhibit translation in vitro. Thus, the results of our studies suggest that hcn RNA degradants are likely to be involved in the regulation of gene expression in plants.