Biology subjects

Vaikkinen, H.

Publications and source records attributed to Vaikkinen, H..

8 recordsLinked to original sources

bioRxiv2026

Innate immune stress pathway activation underlies heterochromatin dysfunction pathology

Heterochromatin loss disrupts nuclear architecture, gene regulation and repetitive element silencing, and is associated with diverse human diseases. However, mechanisms linking heterochromatin dysfunction to pathological phenotypes remain unclear. Using genetic interaction screening and genomic analyses in C. elegans, we identify secondary activation of the Intracellular Pathogen Response (IPR), an innate immune stress pathway, as a major contributor to heterochromatin mutant phenotypes. Constitutive IPR activation phenocopies slow growth and indirect transcriptional changes observed in these mutants. Depletion of genetic enhancers further increased, whereas suppressor RNAi attenuated IPR activation, with direct heterochromatin targets remaining substantially deregulated. Notably, many suppressors encode active chromatin components, and mild reduction of RNA polymerase II activity ameliorates growth defects in C. elegans HP1 mutants and human HP1-deficient cells. Our findings reveal secondary stress response activation as an important mechanism linking heterochromatin dysfunction to pathology and identify transcriptional dampening as a potential therapeutic strategy for mitigating these effects.

genetics↗

bioRxiv2026

An integrated pipeline to count individual transcripts with single-cell resolution

Quantifying transcript abundance at single-cell resolution is important for understanding gene regulation in intact multicellular organisms. In Caenorhabditis elegans, RNA fluorescence in situ hybridization has been widely used to visualize transcripts, but conventional smFISH approaches can be limited by low signal-to-noise, poor performance with short transcripts, and workflows that do not readily support absolute transcript counting in identified cells. Here, we present an integrated experimental and computational pipeline for quantitative transcript analysis in whole-mount C. elegans embryos, larvae, and adults. The pipeline combines Hybridization Chain Reaction (HCR), confocal microscopy, RS-FISH spot detection, manual cell annotation in FIJI, and custom MATLAB-based spot assignment to quantify individual transcripts within defined cells. We show that this approach enables sensitive, specific, and multiplexed detection of transcripts, including short insulin-like peptide mRNAs, with single-cell resolution. Known spatial expression patterns were resolved in embryos, larvae, and adults, and probe specificity was validated using deletion mutants that remove HCR probe-binding sites. Applying this pipeline to ins-4, ins-6, and daf-28 in ASI and ASJ sensory neurons revealed cell-specific and context-dependent regulatory relationships across multiple mutant backgrounds. This workflow provides an accessible method for absolute transcript counting in anatomically intact C. elegans and should support mechanistic studies of gene regulation, cellular heterogeneity, and transcriptional network function.

molecular biology↗

bioRxiv2024

Epigenetic investigation of multifocal small intestinal neuroendocrine tumours reveals accelerated ageing of tumours and epigenetic alteration of metabolic genes

BackgroundSmall intestinal neuroendocrine tumours (SI-NETs) are the most common malignancy of the small intestine and around 50% of patients present in clinic with multifocal disease. Recent investigations into the genomic architecture of multifocal SI-NETs have found evidence that these synchronous primary tumours evolve independently of each other. They also have extremely low mutational burden and few known driver genes, suggesting that epigenetic dysregulation may be driving tumorigenesis. Very little is known about epigenetic gene regulation, metabolism and ageing in these tumours, and how these traits differ across multiple tumours within individual patients. MethodsIn this study, we performed the first investigation of genome-wide DNA methylation in multifocal SI-NETs, assessing multiple primary tumours within each patient (n=79 primary tumours from 14 patients) alongside matched metastatic tumours (n=12) and normal intestinal epithelial tissue (n=9). We assessed multifocal SI-NET differential methylation using a novel method, comparing primary tumours with matched normal epithelial tissue and an enterochromaffin-enriched cell line to enrich for tumour-specific effects. This method reduced the identification of false positive methylation differences driven by cell composition differences between tumour and normal epithelial tissue. We also assessed tumour ageing using epigenetic clocks and applied metabolic predictors in the dataset to assess methylation variation across key metabolic genes. ResultsWe have identified 12,392 tumour-specific differentially methylated positions (Bonferroni corrected p<0.05) which were enriched for neural pathways. The expression levels of the genes associated with top sites were also found to be significantly altered in SI-NETs. Age acceleration was observed across SI-NETs and a variability in epigenetic age of tumours within each patient, which we believe is reflecting the order in which tumours have developed. This is supported by the correlation of age acceleration with somatic mutational count in the tumours. We have identified SI-NET associated alterations to the methylation patterns in key metabolic genes compared to matched normal tissue, which is more pronounced in metastatic tumours and tumours harbouring chromosome 18 loss of heterozygosity, indicating metabolic differences in these tumour subtypes. ConclusionsWe have identified accelerated ageing and changes to regulation of metabolic genes, alongside an epigenetic signature of multifocal SI-NETs. These findings add to our understanding of multifocal SI-NET biology and their molecular differences which may be instrumental in the development of these elusive tumours.

cancer biology↗

bioRxiv2022

Single cell transcriptomic and spatial landscapes of the developing human pancreas

The progress made in directed differentiation of stem cells has shown that understanding human pancreas development can provide cues for generating unlimited amounts of insulin-producing beta cells for transplantation therapy in diabetes. However, current differentiation protocols have not been successful in reproducibly generating functional human beta cells in vitro, partly due to incomplete understanding of human pancreas development. Here, we present detailed transcriptomic analysis of the various cell types of the developing human pancreas, including their spatial gene patterns. We integrated single cell RNA sequencing with spatial transcriptomics at multiple developmental timepoints and revealed distinct temporal-spatial gene cascades in the developing human pancreas. Cell trajectory inference identified endocrine progenitor populations and novel branch-specific genes as the progenitors differentiate towards alpha or beta cells, indicating that transcriptional maturation occurred over this developmental timeframe. Spatial differentiation trajectories indicated that immature Schwann cells are spatially co-located with endocrine progenitors and contribute to beta cell maturation via the L1CAM-EPHB2 pathway. Our integrated approach enabled us to identify heterogeneity and multiple lineage dynamics within the mesenchyme, showing that it contributed to the exocrine acinar cell state. Finally, we have generated an interactive web resource for interrogating human pancreas development for the research community.

developmental biology↗

bioRxiv2021

Performance comparison and in-silico harmonisation of commercial platforms for DNA methylome analysis by targeted bisulfite sequencing

DNA methylation is a key epigenetic modification in the regulation of cell fate and differentiation, and its analysis is gaining increasing importance in both basic and clinical research. Targeted Bisulfite Sequencing (TBS) has become the method of choice for the cost-effective, targeted analysis of the human methylome at base-pair resolution. Here we benchmarked five commercially available TBS platforms, including three hybridization capture-based (Agilent, Roche, and Illumina) and two RRBS-based (Diagenode and NuGen), across 16 samples. A subset of these were also compared to whole-genome DNA methylation sequencing with the Illumina and Oxford Nanopore platforms. We assessed performance with respect to workflow complexity, on/off-target performance, coverage, accuracy and reproducibility. We find all platforms able to produce usable data but major differences for some performance criteria, especially in the number and identity of the CpG sites covered, which affects the interoperability of datasets generated on these different platforms. To overcome this limitation, we used imputation and show that it improves the interoperability from an average of 10.35% (0.8M CpG sites) to 97% (7.6M CpG sites). Our study provides cross-validated guidance on which TBS platform to use for different features of the methylome and offers an imputation-based harmonization solution for improved interoperability between platforms, allowing comparative and integrative analysis.

genomics↗

bioRxiv2020

Copy number-aware deconvolution of tumor-normal DNA methylation profiles

Aberrant methylation is a hallmark of cancer, but bulk tumor data is confounded by admixed normal cells and copy number changes. Here, we introduce Copy number-Aware Methylation Deconvolution Analysis of Cancers (CAMDAC; https://github.com/VanLoo-lab/CAMDAC), which outputs tumor purity, allele-specific copy number and deconvolved methylation estimates. We apply CAMDAC to 122 multi-region samples from 38 TRACERx non-small cell lung cancers profiled by reduced representation bisulfite sequencing. CAMDAC copy number profiles parallel those derived from genome sequencing and highlight widespread chromosomal instability. Deconvolved polymorphism-independent methylation rates enable unbiased tumor-normal and tumor-tumor differential methylation calling. Read-phasing validates CAMDAC methylation rates and directly links genotype and epitype. We show increased epigenetic instability in adenocarcinoma vs. squamous cell carcinoma, frequent hypermethylation at sites carrying somatic mutations, and parallel copy number losses and methylation changes at imprinted loci. Unlike bulk methylomes, CAMDAC profiles recapitulate tumor phylogenies and evidence distinct patterns of epigenetic heterogeneity in lung cancer.

genomics↗

bioRxiv2018

Application of long read sequencing to determine expressed antigen diversity in Trypanosoma brucei infections

AO_SCPLOWBSTRACTC_SCPLOWAntigenic variation is employed by many pathogens to evade the host immune response, and Trypanosoma brucei has evolved a complex system to achieve this phenotype, involving sequential use of variant surface glycoprotein (VSG) genes encoded from a large repertoire of [~]2,000 alleles. T. brucei express multiple, sometimes closely related, VSGs in a population at any one time, and the ability to resolve and analyse this diversity has been limited. We applied long read sequencing (PacBio) to VSG amplicons generated from blood extracted from batches of mice sacrificed at time points (days 3, 6, 10 and 12) post-infection with T. brucei TREU927. The data showed that long read sequencing is reliable for resolving allelic differences between VSGs, and demonstrated that there is significant expressed diversity (449 VSGs detected across 20 mice) and across the timeframe of study there was a clear semi-reproducible pattern of expressed diversity (median of 27 VSGs per sample at day 3 post infection (p.i.), 82 VSGs at day 6 p.i., 187 VSGs at day 10 p.i. and 132 VSGs by day 12 p.i.). There was also consistent detection of one VSG dominating expression across replicates at days 3 and 6, and emergence of a second dominant VSG across replicates by day 12. The innovative application of ecological diversity analysis to VSG reads enabled characterisation of hierarchical VSG expression in the dataset, and resulted in a novel method for analysing such patterns of variation. Additionally, the long read approach allowed detection of mosaic VSG expression from very few reads - this was observed as early as day 3, the earliest that such events have been detected. Therefore, our results indicate that long read analysis is a reliable tool for resolving diverse allele expression profiles, and provides novel insights into the complexity and nature of VSG expression in trypanosomes, revealing significantly higher diversity than previously shown and identifying mosaic gene formation unprecedentedly early during the infection process.

genomics↗

bioRxiv2017

T cell activation and the HLA locus associate with latent infections of human African trypanosomiasis

Infections by many pathogens can result in a wide range of phenotypes, from severe to mild, or even asymptomatic. Understanding the genetic basis of these phenotypes can lead to better tools to treat patients or detect reservoirs. To identify human genetic factors that contribute to symptoms diversity, we examined the range of disease severities caused by the parasite T. b. gambiense, the primary cause of human African trypanosomiasis (HAT). We analyzed the transcriptomes of immune cells from both symptomatic HAT cases and individuals with latent infections. Our analysis identified several genes and pathways that associated with the latent phenotype, primarily suggesting increased T and B cell activation in HAT patients relative to latent infections. We also used these transcriptome data to conduct an exome-wide single nucleotide polymorphism (SNP) association study. This suggested that SNPs in the human major histocompatibility locus (HLA) associate with severity, supporting the transcription data and suggesting that T cell activation is a determining factor in outcome. Finally, to establish if T cell activation controls disease severity, we blocked co-stimulatory dependent T cell activation in an animal model for HAT. This showed that reducing T cell activation during trypanosome infection improves symptoms and reduces parasitemia. Our data has used a combination of transcriptome-wide analysis and an in vivo model to reveal that T cell activation and the HLA locus associate with the development of symptoms during HAT. This may open new avenues for the development of new therapeutics and prognostics.

genetics↗