Development of an optimized, non-stem cell line for intranasal delivery of therapeutic cargo to the central nervous system

Neural stem cells (NSCs) are considered to be valuable candidates for delivering a variety of anti-cancer agents, including oncolytic viruses, to brain tumors. However, owing to the previously reported tumorigenic potential of NSC cell lines after intranasal administration (INA), here we identified the human hepatic stellate cell line LX-2 as a cell type capable of longer resistance to replication of oncolytic adenoviruses (OAVs) as a therapeutic cargo, and that is non-tumorigenic after INA. Our data show that LX-2 cells can longer withstand the OAV XVir-N-31 replication and oncolysis than NSCs. By selecting the highly migratory cell population out of LX-2, an offspring cell line with a higher and more stable capability to migrate was generated. Additionally, as a safety backup, we applied genomic herpes simplex virus thymidine kinase (HSV-TK) integration into LX-2, leading to high vulnerability to ganciclovir (GCV). Histopathological analyses confirmed the absence of neoplasia in the respiratory tracts and brains of immuno-compromised mice 3 months after INA of LX-2 cells. Our data suggest that LX-2 is a novel, robust, and safe cell line for delivering anti-cancer and other therapeutic agents to the brain.

PSF toolkit: an R package for pathway curation and topology-aware analysis

Most high throughput genomic data analysis pipelines currently rely on over-representation or gene set enrichment analysis (ORA/GSEA) approaches for functional analysis. In contrast, topology-based pathway analysis methods, which offer a more biologically informed perspective by incorporating interaction and topology information, have remained underutilized and inaccessible due to various limiting factors. These methods heavily rely on the quality of pathway topologies and often utilize predefined topologies from databases without assessing their correctness. To address these issues and make topology-aware pathway analysis more accessible and flexible, we introduce the PSF (Pathway Signal Flow) toolkit R package. Our toolkit integrates pathway curation and topology-based analysis, providing interactive and command-line tools that facilitate pathway importation, correction, and modification from diverse sources. This enables users to perform topology-based pathway signal flow analysis in both interactive and command-line modes. To showcase the toolkit's usability, we curated 36 KEGG signaling pathways and conducted several use-case studies, comparing our method with ORA and the topology-based signaling pathway impact analysis (SPIA) method. The results demonstrate that the algorithm can effectively identify ORA enriched pathways while providing more detailed branch-level information. Moreover, in contrast to the SPIA method, it offers the advantage of being cut-off free and less susceptible to the variability caused by selection thresholds. By combining pathway curation and topology-based analysis, the PSF toolkit enhances the quality, flexibility, and accessibility of topology-aware pathway analysis. Researchers can now easily import pathways from various sources, correct and modify them as needed, and perform detailed topology-based pathway signal flow analysis. In summary, our PSF toolkit offers an integrated solution that addresses the limitations of current topology-based pathway analysis methods. By providing interactive and command-line tools for pathway curation and topology-based analysis, we empower researchers to conduct comprehensive pathway analyses across a wide range of applications.

Long-term environmental metal exposure is associated with hypomethylation of CpG sites in NFKB1 and other genes related to oncogenesis

BACKGROUND

Long-term environmental exposure to metals leads to epigenetic changes and may increase risks to human health. The relationship between the type and level of metal exposure and epigenetic changes in subjects exposed to high concentrations of metals in the environment is not yet clear. The aim of our study is to find the possible association of environmental long-term exposure to metals with DNA methylation changes of genes related to immune response and carcinogenesis. We investigated the association of plasma levels of 21 essential and non-essential metals detected by ICP-MS and the methylation level of 654 CpG sites located on NFKB1, CDKN2A, ESR1, APOA5, IGF2 and H19 genes assessed by targeted bisulfite sequencing in a cohort of 40 subjects living near metal mining area and 40 unexposed subjects. Linear regression was conducted to find differentially methylated positions with adjustment for gender, age, BMI class, smoking and metal concentration.

RESULTS

In the metal-exposed group, five CpGs in the NFKB1 promoter region were hypomethylated compared to unexposed group. Four differentially methylated positions (DMPs) were associated with multiple metals, two of them are located on NFKB1 gene, and one each on CDKN2A gene and ESR1 gene. Two DMPs located on NFKB1 (chr4:102500951, associated with Be) and IGF2 (chr11:2134198, associated with U) are associated with specific metal levels. The methylation status of the seven CpGs located on NFKB1 (3), ESR1 (2) and CDKN2A (2) positively correlated with plasma levels of seven metals (As, Sb, Zn, Ni, U, I and Mn).

CONCLUSIONS

Our study revealed methylation changes in NFKB1, CDKN2A, IGF2 and ESR1 genes in individuals with long-term human exposure to metals. Further studies are needed to clarify the effect of environmental metal exposure on epigenetic mechanisms and pathways involved.

Molecular Analysis of SARS-CoV-2 Lineages in Armenia

The sequencing of SARS-CoV-2 provides essential information on viral evolution, transmission, and epidemiology. In this paper, we performed the whole-genome sequencing of SARS-CoV-2 using nanopore and Illumina sequencing to describe the circulation of the virus lineages in Armenia. The analysis of 145 full genomes identified six clades (19A, 20A, 20B, 20I, 21J, and 21K) and considerable intra-clade PANGO lineage diversity. Phylodynamic and transmission analysis allowed to attribute specific clades as well as infer their importation routes. Thus, the first two waves of positive case increase were caused by the 20B clade, the third peak caused by the 20I (Alpha), while the last two peaks were caused by the 21J (Delta) and 21K (Omicron) variants. The functional analyses of mutations in sequences largely affected epitopes associated with protective HLA loci and did not cause the loss of the signal in PCR tests targeting ORF1ab and N genes as confirmed by RT-PCR. We also compared the performance of nanopore and Illumina short-read sequencing and showed the utility of nanopore sequencing as an efficient and affordable alternative for large-scale molecular epidemiology research. Thus, our paper describes new data on the genomic diversity of SARS-CoV-2 variants in Armenia in the global context of the virus molecular genomic surveillance.

The Evolving Faces of the SARS-CoV-2 Genome

Surveillance of the evolving SARS-CoV-2 genome combined with epidemiological monitoring and emerging vaccination became paramount tasks to control the pandemic which is rapidly changing in time and space. Genomic surveillance must combine generation and sharing sequence data with appropriate bioinformatics monitoring and analysis methods. We applied molecular portrayal using self-organizing maps machine learning (SOM portrayal) to characterize the diversity of the virus genomes, their mutual relatedness and development since the beginning of the pandemic. The genetic landscape obtained visualizes the relevant mutations in a lineage-specific fashion and provides developmental paths in genetic state space from early lineages towards the variants of concern alpha, beta, gamma and delta. The different genes of the virus have specific footprints in the landscape reflecting their biological impact. SOM portrayal provides a novel option for 'bioinformatics surveillance' of the pandemic, with strong odds regarding visualization, intuitive perception and 'personalization' of the mutational patterns of the virus genomes.

A Transcriptome-Wide Isoform Landscape of Melanocytic Nevi and Primary Melanomas Identifies Gene Isoforms Associated with Malignancy

Genetic splice variants have become of central interest in recent years, as they play an important role in different cancers. Little is known about splice variants in melanoma. Here, we analyzed a genome-wide transcriptomic dataset of benign melanocytic nevi and primary melanomas (n = 80) for the expression of specific splice variants. Using kallisto, a map for differentially expressed splice variants in melanoma vs. benign melanocytic nevi was generated. Among the top genes with differentially expressed splice variants were Ras-related in brain 6B (RAB6B), a member of the RAS family of GTPases, Macrophage Scavenger Receptor 1 (MSR1), Collagen Type XI Alpha 2 Chain (COLL11A2), and LY6/PLAUR Domain Containing 1 (LYPD1). The Gene Ontology terms of differentially expressed splice variants showed no enrichment for functional gene sets of melanoma vs. nevus lesions, but between type 1 (pigmentation type) and type 2 (immune response type) melanocytic lesions. A number of genes such as Checkpoint Kinase 1 (CHEK1) showed an association of mutational patterns and occurrence of splice variants in melanoma. Moreover, mutations in genes of the splicing machinery were common in both benign nevi and melanomas, suggesting a common mechanism starting early in melanoma development. Mutations in some of these genes of the splicing machinery, such as Serine and Arginine Rich Splicing Factor A3 and B3 (SF3A3, SF3B3), were significantly enriched in melanomas as compared to benign nevi. Taken together, a map of splice variants in melanoma is presented that shows a multitude of differentially expressed splice genes between benign nevi and primary melanomas. The underlying mechanisms may involve mutations in genes of the splicing machinery.

High-Resolution Cartography of the Transcriptome and Methylome Landscapes of Diffuse Gliomas

Molecular mechanisms of lower-grade (II-III) diffuse gliomas (LGG) are still poorly understood, mainly because of their heterogeneity. They split into astrocytoma- (IDH-A) and oligodendroglioma-like (IDH-O) tumors both carrying mutations(s) at the isocitrate dehydrogenase (IDH) gene and into IDH wild type (IDH-wt) gliomas of glioblastoma resemblance. We generated detailed maps of the transcriptomes and DNA methylomes, revealing that cell functions divided into three major archetypic hallmarks: (i) increased proliferation in IDH-wt and, to a lesser degree, IDH-O; (ii) increased inflammation in IDH-A and IDH-wt; and (iii) the loss of synaptic transmission in all subtypes. Immunogenic properties of IDH-A are diverse, partly resembling signatures observed in grade IV mesenchymal glioblastomas or in grade I pilocytic astrocytomas. We analyzed details of coregulation between gene expression and DNA methylation and of the immunogenic micro-environment presumably driving tumor development and treatment resistance. Our transcriptome and methylome maps support personalized, case-by-case views to decipher the heterogeneity of glioma states in terms of data portraits. Thereby, molecular cartography provides a graphical coordinate system that links gene-level information with glioma subtypes, their phenotypes, and clinical context.

Transcriptome Patterns of BRCA1- and BRCA2- Mutated Breast and Ovarian Cancers

Mutations in the BRCA1 and BRCA2 genes are known risk factors and drivers of breast and ovarian cancers. So far, few studies have been focused on understanding the differences in transcriptome and functional landscapes associated with the disease (breast vs. ovarian cancers), gene (BRCA1 vs. BRCA2), and mutation type (germline vs. somatic). In this study, we were aimed at systemic evaluation of the association of BRCA1 and BRCA2 germline and somatic mutations with gene expression, disease clinical features, outcome, and treatment. We performed BRCA1/2 mutation centered RNA-seq data analysis of breast and ovarian cancers from the TCGA repository using transcriptome and phenotype "portrayal" with multi-layer self-organizing maps and functional annotation. The results revealed considerable differences in BRCA1- and BRCA2-dependent transcriptome landscapes in the studied cancers. Furthermore, our data indicated that somatic and germline mutations for both genes are characterized by deregulation of different biological functions and differential associations with phenotype characteristics and poly(ADP-ribose) polymerase (PARP)-inhibitor gene signatures. Overall, this study demonstrates considerable variation in transcriptomic landscapes of breast and ovarian cancers associated with the affected gene (BRCA1 vs. BRCA2), as well as the mutation type (somatic vs. germline). These results warrant further investigations with larger groups of mutation carriers aimed at refining the understanding of molecular mechanisms of breast and ovarian cancers.

oposSOM-Browser: an interactive tool to explore omics data landscapes in health science

BACKGROUND

oposSOM is a comprehensive, machine learning based open-source data analysis software combining functionalities such as diversity analyses, biomarker selection, function mining, and visualization.

RESULTS

These functionalities are now available as interactive web-browser application for a broader user audience interested in extracting detailed information from high-throughput omics data sets pre-processed by oposSOM. It enables interactive browsing of single-gene and gene set profiles, of molecular 'portrait landscapes', of associated phenotype diversity, and signalling pathway activation patterns.

CONCLUSION

The oposSOM-Browser makes available interactive data browsing for five transcriptome data sets of cancer (melanomas, B-cell lymphomas, gliomas) and of peripheral blood (sepsis and healthy individuals) at www.izbi.uni-leipzig.de/opossom-browser .

Transcriptome-Guided Drug Repositioning

Drug repositioning can save considerable time and resources and significantly speed up the drug development process. The increasing availability of drug action and disease-associated transcriptome data makes it an attractive source for repositioning studies. Here, we have developed a transcriptome-guided approach for drug/biologics repositioning based on multi-layer self-organizing maps (ml-SOM). It allows for analyzing multiple transcriptome datasets by segmenting them into layers of drug action- and disease-associated transcriptome data. A comparison of expression changes in clusters of functionally related genes across the layers identifies "drug target" spots in disease layers and evaluates the repositioning possibility of a drug. The repositioning potential for two approved biologics drugs (infliximab and brodalumab) confirmed the drugs' action for approved diseases (ulcerative colitis and Crohn's disease for infliximab and psoriasis for brodalumab). We showed the potential efficacy of infliximab for the treatment of sarcoidosis, but not chronic obstructive pulmonary disease (COPD). Brodalumab failed to affect dysregulated functional gene clusters in Crohn's disease (CD) and systemic juvenile idiopathic arthritis (SJIA), clearly indicating that it may not be effective in the treatment of these diseases. In conclusion, ml-SOM offers a novel approach for transcriptome-guided drug repositioning that could be particularly useful for biologics drugs.

Population Levels Assessment of the Distribution of Disease-Associated Variants With Emphasis on Armenians - A Machine Learning Approach

Background: During the last decades a number of genome-wide association studies (GWASs) has identified numerous single nucleotide polymorphisms (SNPs) associated with different complex diseases. However, associations reported in one population are often conflicting and did not replicate when studied in other populations. One of the reasons could be that most GWAS employ a case-control design in one or a limited number of populations, but little attention was paid to the global distribution of disease-associated alleles across different populations. Moreover, the majority of GWAS have been performed on selected European, African, and Chinese populations and the considerable number of populations remains understudied. Aim: We have investigated the global distribution of so far discovered disease-associated SNPs across worldwide populations of different ancestry and geographical regions with a special focus on the understudied population of Armenians. Data and Methods: We have used genotyping data from the Human Genome Diversity Project and of Armenian population and combined them with disease-associated SNP data taken from public repositories leading to a final dataset of 44,234 markers. Their frequency distribution across 1039 individuals from 53 populations was analyzed using self-organizing maps (SOM) machine learning. Our SOM portrayal approach reduces data dimensionality, clusters SNPs with similar frequency profiles and provides two-dimensional data images which enable visual evaluation of disease-associated SNPs landscapes among human populations. Results: We find that populations from Africa, Oceania, and America show specific patterns of minor allele frequencies of disease-associated SNPs, while populations from Europe, Middle East, Central South Asia, and Armenia mostly share similar patterns. Importantly, different sets of SNPs associated with common polygenic diseases, such as cancer, diabetes, neurodegeneration in populations from different geographic regions. Armenians are characterized by a set of SNPs that are distinct from other populations from the neighboring geographical regions. Conclusion: Genetic associations of diseases considerably vary across populations which necessitates health-related genotyping efforts especially for so far understudied populations. SOM portrayal represents novel promising methods in population genetic research with special strength in visualization-based comparison of SNP data.

Complement activation in leprosy: a retrospective study shows elevated circulating terminal complement complex in reactional leprosy

Mycobacterium leprae infection gives rise to the immunologically and histopathologically classified spectrum of leprosy. At present, several tools for the stratification of patients are based on acquired immunity markers. However, the role of innate immunity, particularly the complement system, is largely unexplored. The present retrospective study was undertaken to explore whether the systemic levels of complement activation components and regulators can stratify leprosy patients, particularly in reference to the reactional state of the disease. Serum samples from two cohorts were analysed. The cohort from Bangladesh included multi-bacillary (MB) patients with (n = 12) or without (n = 46) reaction (R) at intake and endemic controls (n = 20). The cohort from Ethiopia included pauci-bacillary (PB) (n = 7) and MB (n = 23) patients without reaction and MB (n = 15) patients with reaction. The results showed that the activation products terminal complement complex (TCC) (P ≤ 0·01), C4d (P ≤ 0·05) and iC3b (P ≤ 0·05) were specifically elevated in Bangladeshi patients with reaction at intake compared to endemic controls. In addition, levels of the regulator clusterin (P ≤ 0·001 without R; P < 0·05 with R) were also elevated in MB patients, irrespective of a reaction. Similar analysis of the Ethiopian cohort confirmed that, irrespective of a reaction, serum TCC levels were increased significantly in patients with reactions compared to patients without reactions (P ≤ 0·05). Our findings suggests that serum TCC levels may prove to be a valuable tool in diagnosing patients at risk of developing reactions.

Green-diode-pumped femtosecond Ti:Sapphire laser with up to 450 mW average power

We investigate power-scaling of green-diode-pumped Ti:Sapphire lasers in continuous-wave (CW) and mode-locked operation. In a first configuration with a total pump power of up to 2 W incident onto the crystal, we achieved a CW power of up to 440 mW and self-starting mode-locking with up to 200 mW average power in 68-fs pulses using semiconductor saturable absorber mirror (SESAM) as saturable absorber. In a second configuration with up to 3 W of pump power incident onto the crystal, we achieved up to 650 mW in CW operation and up to 450 mW in 58-fs pulses using Kerr-lens mode-locking (KLM). The shortest pulse duration was 39 fs, which was achieved at 350 mW average power using KLM. The mode-locked laser generates a pulse train at repetition rates around 400 MHz. No complex cooling system is required: neither the SESAM nor the Ti:Sapphire crystal is actively cooled, only air cooling is applied to the pump diodes using a small fan. Because of mass production for laser displays, we expect that prices for green laser diodes will become very favorable in the near future, opening the door for low-cost Ti:Sapphire lasers. This will be highly attractive for potential mass applications such as biomedical imaging and sensing.

Systemic complement profiling in multiple sclerosis as a biomarker of disease state

BACKGROUND

There is increasing evidence of significant and dynamic systemic activation and upregulation of complement in multiple sclerosis (MS), which may contribute to disease pathogenesis.

OBJECTIVE

We aimed to investigate the pathological role of complement in MS and the potential role for complement profiling as a biomarker of MS disease state.

METHODS

Key components of the classical, alternative and terminal pathways of complement were measured in plasma and cerebrospinal fluid (CSF) of patients with MS in different clinical phases of disease and in matched controls.

RESULTS

Increased plasma levels of C3 (p<0.003), C4 (p<0.001), C4a (p<0.001), C1 inhibitor (p<0.001), and factor H (p<0.001), and reduced levels of C9 (p<0.001) were observed in MS patients compared with controls. Combined profiling of these analytes produced a statistical model with a predictive value of 97% for MS and 73% for clinical relapse when combined with selected demographic data. CSF-plasma correlations suggested that source of synthesis of these components was both systemic and central.

CONCLUSION

These data provide further evidence of alterations in both local and systemic expression and activation of complement in MS and suggest that complement profiling may be informative as a biomarker of MS disease, although further work is needed to determine its use in distinguishing MS from its differential.

Variation in complement component C1 inhibitor in age-related macular degeneration

This study assessed variation in plasma levels of the complement regulatorC1 inhibitor (C1inh) in patients with age related macular degeneration (AMD) and controls. Plasma from391 AMD cases and 370 controls was assayed by rate nephelometry to determine C1inh protein levels. Protein levels were analysed for relationships with age, gender, smoking, AMD disease status and genetic variation in the SERPING1 gene, which encodes C1inh, using a multivariate analysis. t-Tests show a significant difference in C1inh levels in AMD cases compared with controls (p=2.340E-6), smokers compared to non-smokers (p=1.022E-4) and females compared to males (p=1.661E-7). Multivariate analysis shows that after accounting for gender and smoking AMD status remained significant. Age was included in the model but was not significant. Including genetic variation in the model shows that one significant SNP (rs2649663) 5' of the SERPING1 gene is associated with C1inh levels though this SNP is not associated with AMD. This suggests that genetic variation in the promoter region of the SERPING1 gene may influence expression of the gene.

Complement in multiple sclerosis: its role in disease and potential as a biomarker

Multiple sclerosis (MS) is a common inflammatory disease of the central nervous system with a poorly defined and complex immunopathogenesis. Although initiated by reactive T cells, persistent inflammation is evident throughout the disease course. A contribution from complement has long been suspected, based on the results of pathological and functional studies which have demonstrated complement activation products in MS brain and biological fluids. However, the extent and nature of complement activation and its contribution to disease phenotype and long-term outcome remain unclear. Furthermore, functional polymorphisms in components and regulators of the complement system which cause dysregulation, and are known to contribute to other autoimmune inflammatory disorders, have not been investigated to date in MS in any detail. In this paper we review evidence from pathological, animal model and human functional and genetic studies, implicating activation of complement in MS. We also evaluate the potential of complement components and regulators and their polymorphic variants as biomarkers of disease, and suggest appropriate directions for future research.