Browsing by Subject "Bioinformatics"

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  • Guirado, Ramon; Carceller, Hector; Castillo-Gomez, Esther; Castren, Eero; Nacher, Juan (2018)
    The quantification of the expression of different molecules is a key question in both basic and applied sciences. While protein quantification through molecular techniques leads to the loss of spatial information and resolution, immunohistochemistry is usually associated with time-consuming image analysis and human bias. In addition, the scarce automatic software analysis is often proprietary and expensive and relies on a fixed threshold binarization. Here we describe and share a set of macros ready for automated fluorescence analysis of large batches of fixed tissue samples using FIJI/ImageJ. The quantification of the molecules of interest are based on an automatic threshold analysis of immunofluorescence images to automatically identify the top brightest structures of each image. These macros measure several parameters commonly quantified in basic neuroscience research, such as neuropil density and fluorescence intensity of synaptic puncta, perisomatic innervation and col-localization of different molecules and analysis of the neurochemical phenotype of neuronal subpopulations. In addition, these same macro functions can be easily modified to improve similar analysis of fluorescent probes in human biopsies for diagnostic purposes based on the expression patterns of several molecules.
  • Pfeifer, Marion; Lefebvre, Veronique; Gardner, Toby A.; Arroyo-Rodriguez, Victor; Baeten, Lander; Banks-Leite, Cristina; Barlow, Jos; Betts, Matthew G.; Brunet, Joerg; Cerezo, Alexis; Cisneros, Laura M.; Collard, Stuart; D'Cruze, Neil; da Silva Motta, Catarina; Duguay, Stephanie; Eggermont, Hilde; Eigenbrod, Felix; Hadley, Adam S.; Hanson, Thor R.; Hawes, Joseph E.; Scalley, Tamara Heartsill; Klingbeil, Brian T.; Kolb, Annette; Kormann, Urs; Kumar, Sunil; Lachat, Thibault; Lakeman Fraser, Poppy; Lantschner, Victoria; Laurance, William F.; Leal, Inara R.; Lens, Luc; Marsh, Charles J.; Medina-Rangel, Guido F.; Melles, Stephanie; Mezger, Dirk; Oldekop, Johan A.; Overal, William L.; Owen, Charlotte; Peres, Carlos A.; Phalan, Ben; Pidgeon, Anna M.; Pilia, Oriana; Possingham, Hugh P.; Possingham, Max L.; Raheem, Dinarzarde C.; Ribeiro, Danilo B.; Ribeiro Neto, Jose D.; Robinson, W. Douglas; Robinson, Richard; Rytwinski, Trina; Scherber, Christoph; Slade, Eleanor M.; Somarriba, Eduardo; Stouffer, Philip C.; Struebig, Matthew J.; Tylianakis, Jason M.; Tscharntke, Teja; Tyre, Andrew J.; Urbina Cardona, Jose N.; Vasconcelos, Heraldo L.; Wearn, Oliver; Wells, Konstans; Willig, Michael R.; Wood, Eric; Young, Richard P.; Bradley, Andrew V.; Ewers, Robert M. (2014)
  • Amiryousefi, Ali (Helsingin yliopisto, 2019)
    Chloroplasts are cytoplasmic organelles chiefly responsible for the photosynthesis. Their genes have been used extensively during the past decades in phylogenetic analyses of various photosynthetic eukaryotes, particularly plants. The genomic content of this organelle and its very architecture can be used for a deeper insight in evolution and towards robust phylogenetic hypotheses. Ever since this importance was recognized concurrently with the advancements of methods in both providing a basic genetic material through sequencing and advanced methods to analyze the data, we have witnessed the introduction of a couple of thousands plastid genomes up to this date. This process, by no means is in its decline or even stationary state, as this pace is projected to be accelerated in the coming years, with the inevitable advances in our technologies and our need to understand the nature as accurate as possible. The aim of this study as represented in the sequel chapters is twofold; 1) to introduce the complete chloroplast genomes of two species from the euasterid clade and provide their phylogenetic analyses; Solanum dulcamara L. as a native Old World diploid member of the nightshade family, and Ambrosia trifida L. as a recognized invasive plant originated and evolved from North America. 2) To provide two analytical tools for more advanced treatment of the genetic information of plastids in bioinformatics. By comparative analysis for bittersweet and giant ragweed, the result show that synteny and the genomic content of both belonging to the families Solanaceae and Asteraceae, respectively, have a conserved structure. We also noted that many submitted annotations in the nightshade family are far from acceptable quality, and further on, we improved them with reannotation of the existing sequences. On the other hand, a novel tool (IRscope) to detect and plot the Inverted Repeat (IR) regions of the chloroplast genome was introduced. IRscope, with the help of iterative search algorithm, allows the depiction of genes in the vicinity of the Junction Sites (JS), of up to ten different chloroplast genomes of embryophytes (land plants). Moreover, we constructed an online calculative suite (iMEC) to return the result of the seven different molecular markers against the provided input file. This tool is useful particularly in studies aimed to assess the efficiency of different marker systems linked to plastid genome variation.
  • Icay-Rouhiainen, Katherine (Helsingin yliopisto, 2018)
    All genetic information necessary for creating and maintaining life is stored in DNA and RNA molecules. Gene expression is the process by which sets of DNA (i.e. genes) are encoded into functional gene products. Thus, the state and function of a single cell can be determined by the amount and type of genes expressed: tumour cells can be detected from normal cells, and one functional brain region can be differentiated from another. The discovery of non-coding RNAs like microRNAs (miRNAs) introduced a sophisticated level of gene regulation to our understanding of the flow of genetic information. Strong evidence suggest miRNAs have vital roles in mediating a wide range of biological pathways essential to cell maintenance and tissue-specific function. In complex diseases such as cancer, they show particular promise as candidate biomarkers in prognosis, diagnosis, and treatment. However, we are still uncertain about the precise mechanisms and contributions of miRNAs in regulating gene expression. High-throughput technologies generate molecular data of unprecedented size and depth, providing unique opportunities to study small RNA molecules and complex diseases. Despite exact regulatory mechanisms being uncertain, miRNAs are functionally characterized with high-throughput expression data and the biological pathways annotated to their putative target genes. However, the sheer size of the data generated and to be processed raises challenges in computational resources and in discovering clinically relevant information. This work addresses these challenges with the development and application of two computational tools to better facilitate miRNA research. SePIA is a high-throughput workflow to reliably process sequencing data and perform expression analysis to identify strongly-related miRNAs and their predicted target genes. Director is a visualization package to further the interpretation of molecular interactions and depict the co-regulatory behaviour of miRNAs. The usefulness of these tools is shown in the application of two biomedical studies: in differentiating brain tissue phenotypes, and in determining a role in the chemosensitivity of diffuse large B-cell lymphoma. Sufficient biological context is drawn from the computational results generated by the tools to hypothesize and experimentally validate the role of miRNAs, and propose a set as candidate biomarkers and targets for drug therapy. SePIA and Director are readily available tools developed to improve and make more convenient the computational analysis of miRNAs in biomedical research.
  • Kumar, Ajay Anand; Holm, Liisa; Toronen, Petri (2013)
  • Adunola, Paul Motunrayo (Helsingin yliopisto, 2021)
    Lipoxygenase enzymes, which contribute significantly to storage protein in legume seeds have been reported to cause the emission of volatile compounds associated with the generation of off-flavours. This is an are important factor limiting the acceptance of faba bean (Vicia faba) I foods. This study aimed at using bioinformatic tools to identify seed-borne lipoxygenase (LOX) genes and to design a biological tool using molecular techniques to find changes in sequence in faba bean lines. LOX gene mining by Exonerate sequence comparison on the whole genome sequence of faba bean was used to identify six LOX genes containing Polycystin-1, Lipoxygenase, Alpha-Toxin (PLAT) and/or LH2 LOX domains. Their sequence properties, evolutionary relationships, important conserved LOX motifs and subcellular location were analysed. The LOX gene proteins identified contained 272 – 853 amino acids (aa). The molecular weight ranged from 23.67 kDa in Gene 6 to 96.45 kDA in Gene 1. All the proteins had isoelectric points in the acidic range except Genes 6 and 7 which were alkaline. Only one gene had both LOX conserved domains with aa sequence length similar with that found in soybean and pea LOX genes and isoelectric properties with soybean LOX3. Phylogenetic analysis indicated that the genes were clustered into 9S LOX and 13S LOX types alongside other seed LOX genes in some legumes. Five motifs were found, and sequence analysis showed that three genes (Gene 1, 2 and 3) contained the 38-aa residue motif that includes five histidine residues [His-(X)4-His-(X)4-His-(X)17-His-(X)8-His]. The subcellular localization of the lipoxygenase proteins was predicted to be primarily the cytoplasm and chloroplast. Primers covering ~1.2 kb were designed, based on the conserved region of Genes 1, 2 and 3 nucleotide sequences. Gel electrophoresis showed the PCR amplification of the seed LOX gene at the expected region for twelve faba bean lines. Phylogenetic analysis showed evolutionary divergence among faba bean lines for sequenced and amplified region of their respective seed LOX alleles.
  • Tripathi, Shivanshi (Helsingin yliopisto, 2020)
    Multiple Myeloma (MM) is the second most common hematologic malignancy. Despite the advancements in treatment approaches in the last decade, the prevalence of refractory disease leading to relapsed cases has been a major challenge. A wide range of intricate genetic heterogeneity demonstrated by myeloma patients is a credible explanation for the diverse treatment responses observed in patients sharing the same treatment regimens. Pertaining to this, the study aims to identify predictive gene expression biomarkers that forecast response to BCL2 inhibitor venetoclax and treatment outcome to proteasome inhibitor bortezomib. In this study, samples from MM patients were characterized into sensitive and resistant, (1) based on ex vivo response to venetoclax treatment (Resistant n=21; Sensitive n=21), and (2) based on their bortezomib treatment outcome in clinical profiles (Resistant n=12; Sensitive n=15). Associations between the different gene expressions and drug responses were studied using statistical and bioinformatic tools. As a result, we identified that significant (p-value <0.05) overexpression of 36 genes and downregulation of 38 genes appeared to confer resistance to venetoclax drug response in MM patients. Additionally, the functional association of these genes with pathways was determined using a pathway enrichment tool. Furthermore, the study provided evidence that cytogenetic alterations t(11;14) and t(4;14) are significantly (p-value <0.05) associated with differing venetoclax response in MM patients. These findings demonstrated that gene expression biomarkers and chromosomal translocations play a significant role in regulating venetoclax drug response in MM, which can be further utilized to personalize treatments for patients. The knowledge obtained from this work best applies in personalized medicine; whereby fitting treatments to an individual patient’s genomic landscape will enhance patient outcome.
  • Podpecan, Vid; Ramšak, Živa; Gruden, Kristina; Toivonen, Hannu; Lavrac, Nada (2019)
  • Loetsch, Joern; Sipilä, Reetta; Tasmuth, Tiina; Kringel, Dario; Estlander, Ann-Mari; Meretoja, Tuomo; Kalso, Eija; Ultsch, Alfred (2018)
    Background Prevention of persistent pain following breast cancer surgery, via early identification of patients at high risk, is a clinical need. Supervised machine-learning was used to identify parameters that predict persistence of significant pain. Methods Over 500 demographic, clinical and psychological parameters were acquired up to 6 months after surgery from 1,000 women (aged 28-75 years) who were treated for breast cancer. Pain was assessed using an 11-point numerical rating scale before surgery and at months 1, 6, 12, 24, and 36. The ratings at months 12, 24, and 36 were used to allocate patents to either "persisting pain" or "non-persisting pain" groups. Unsupervised machine learning was applied to map the parameters to these diagnoses. Results A symbolic rule-based classifier tool was created that comprised 21 single or aggregated parameters, including demographic features, psychological and pain-related parameters, forming a questionnaire with "yes/no" items (decision rules). If at least 10 of the 21 rules applied, persisting pain was predicted at a cross-validated accuracy of 86% and a negative predictive value of approximately 95%. Conclusions The present machine-learned analysis showed that, even with a large set of parameters acquired from a large cohort, early identification of these patients is only partly successful. This indicates that more parameters are needed for accurate prediction of persisting pain. However, with the current parameters it is possible, with a certainty of almost 95%, to exclude the possibility of persistent pain developing in a woman being treated for breast cancer.
  • Duru, Ilhan Cem; Laine, Pia Kati Sofia; Andreevskaya, Margarita; Paulin, Lars Göran; Kananen, Soila; Tynkkynen, Soile; Auvinen, Petri Olli Viljami; Smolander, Olli-Pekka Aukusti (2018)
    In Swiss-type cheeses, characteristic nut-like and sweet flavor develops during the cheese ripening due to the metabolic activities of cheese microbiota. Temperature changes during warm and cold room ripening, and duration of ripening can significantly change the gene expression of the cheese microbiota, which can affect the flavor formation. In this study, a metagenomic and metatranscriptomic analysis of Swiss-type Maasdam cheese was performed on samples obtained during ripening in the warm and cold rooms. We reconstructed four different bacterial genomes (Lactococcus lactis, Lactobacillus rhamnosus, Lactobacillus helveticus, and Propionibacterium freudenreichii subsp. shermanii strain JS) from the Maasdam cheese to near completeness. Based on the DNA and RNA mean coverage, Lc. lactis strongly dominated (similar to 80-90%) within the cheese microbial community. Genome annotation showed the potential for the presence of several flavor forming pathways in these species, such as production of methanethiol, free fatty acids, acetoin, diacetyl, acetate, ethanol, and propionate. Using the metatranscriptomic data, we showed that, with the exception of Lc. lactis, the central metabolism of the microbiota was downregulated during cold room ripening suggesting that fewer flavor compounds such as acetoin and propionate were produced. In contrast, Lc. lactis genes related to the central metabolism, including the vitamin biosynthesis and homolactic fermentation, were upregulated during cold room ripening.
  • Korvala, Johanna; Jee, Kowan; Porkola, Emmi; Almangush, Alhadi; Mosakhani, Neda; Bitu, Carolina; Cervigne, Nilva K.; Zandonadi, Flavia S.; Meirelles, Gabriela V.; Paes Leme, Adriana Franco; Coletta, Ricardo D.; Leivo, Ilmo; Salo, Tuula (2017)
    Complex molecular pathways regulate cancer invasion. This study overviewed proteins and microRNAs (miRNAs) involved in oral tongue squamous cell carcinoma (OTSCC) invasion. The human highly aggressive OTSCC cell line HSC-3 was examined in a 3D organotypic human leiomyoma model. Non-invasive and invasive cells were laser-captured and protein expression was analyzed using mass spectrometry-based proteomics and miRNA expression by microarray. In functional studies the 3D invasion assay was replicated after silencing candidate miRNAs, miR-498 and miR-940, in invasive OTSCC cell lines (HSC-3 and SCC-15). Cell migration, proliferation and viability were also studied in the silenced cells. In HSC-3 cells, 67 proteins and 53 miRNAs showed significant fold-changes between non-invasive vs. invasive cells. Pathway enrichment analyses allocated "Focal adhesion" and "ECM-receptor interaction" as most important for invasion. Significantly, in HSC-3 cells, miR-498 silencing decreased the invasion area and miR-940 silencing reduced invasion area and depth. Viability, proliferation and migration weren't significantly affected. In SCC-15 cells, down-regulation of miR-498 significantly reduced invasion and migration. This study shows HSC-3 specific miRNA and protein expression in invasion, and suggests that miR-498 and miR-940 affect invasion in vitro, the process being more influenced by mir-940 silencing in aggressive HSC-3 cells than in the less invasive SCC-15.
  • Sablok, Gaurav; He, Xiaolan; Miranto, Mari Johanna; Flores, Jorge Rafael; Peltomaa, Elina Talvikki; Sleith, Robin; Karol, Kenneth; Delwiche, Charles; Bell, Neil; Paulin, Lars Göran; Poczai, Péter; Hyvönen, Jaakko Tapani (2019)
    Agricultural productivity is a growing concern and several key genomes have been sequenced with the goal of exploring how traits of genomic adaptation could be transferred to cultivated crops, this having been the cornerstone of crop research. Much of the focus has been on crop species that have been directly used to address human needs, considering projected population growth up until 2050 and beyond. However, it is likely that a deeper understanding of mechanisms that could be used to engineer crops will come from the study of early embryophytes (land plants) and closely related freshwater green algae, traits from which could be exploited to boost crop productivity in terms of genomic adaptation with a view towards understanding the basic building blocks of crop engineering. We present the mitogenome of Blasia pusilla (an early embryophyte), assembled using PACBIO SMRT and Illumina sequencing and highlights its role from the phylogenetic perspective.
  • Raitio, Olli Antero; Juslén, Aino; Sirkiä, Päivi; Lehikoinen, Aleksi; Tähtinen, Marko; Piirainen, Esko; Riihikoski, Ville-Matti (2019)
  • Ravantti, Janne; Martinez-Castillo, Ane; Abrescia, Nicola (2020)
    Superimposition of protein structures is key in unravelling structural homology across proteins whose sequence similarity is lost. Structural comparison provides insights into protein function and evolution. Here, we review some of the original findings and thoughts that have led to the current established structure-based phylogeny of viruses: starting from the original observation that the major capsid proteins of plant and animal viruses possess similar folds, to the idea that each virus has an innate “self”. This latter idea fueled the conceptualization of the PRD1-adenovirus lineage whose members possess a major capsid protein (innate “self”) with a double jelly roll fold. Based on this approach, long-range viral evolutionary relationships can be detected allowing the virosphere to be classified in four structure-based lineages. However, this process is not without its challenges or limitations. As an example of these hurdles, we finally touch on the difficulty of establishing structural “self” traits for enveloped viruses showcasing the coronaviruses but also the power of structure-based analysis in the understanding of emerging viruses
  • Kumar, Ashwini (Helsingin yliopisto, 2019)
    This thesis is comprised of three studies demonstrating the application of different statistical and bioinformatic approaches to address distinct challenges of implementing precision medicine strategies for hematological malignancies. The approaches focus on the analysis of next-generation sequencing data, including both genomic and transcriptomics, to deconvolute disease biology and underlying mechanisms of drug sensitivities and resistance. The outcomes of the studies have clinical implications for advancing current diagnosis and treatment paradigms in patients with hematological diseases. Study I, RNA sequencing has not been widely adopted in a clinical diagnostic setting due to continuous development and lack of standardization. Here, the aim was to evaluate the efficiency of two different RNA-seq library preparation protocols applied to cells collected from acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) patients. The poly-A-tailed mRNA selection (PA) and ribo- depletion (RD) based RNA-seq library preparation protocols were compared and evaluated for detection of gene fusions, variant calling and gene expression profiling. Overall, both protocols produced broadly consistent results and similar outcomes. However, the PA protocol was more efficient in quantifying expression of leukemia marker genes and drug targets. It also provided higher sensitivity and specificity for expression-based classification of leukemia. In contrast, the RD protocol was more suitable for gene fusion detection and captured a greater number of transcripts. Importantly, high technical variations were observed in samples from two leukemia patient cases suggesting further development of strategies for transcriptomic quantification and data analysis. Study II, the BCL-2 inhibitor venetoclax is an approved and effective agent in combination with hypomethylating agents or low dose cytarabine for AML patients, unfit for intensive induction chemotherapy. However, a limited number of patients responding to venetoclax and development of resistance to the treatment presents a challenge for using the drug to benefit the majority of the AML patients. The aim was to investigate genomic and transcriptomic biomarkers for venetoclax sensitivity and enable identification of the patients who are most responsive to venetoclax treatment. We found that venetoclax sensitive samples are enriched with WT1 and IDH1/IDH2 mutations. Intriguingly, HOX family genes, including HOXB9, HOXA5, HOXB3, HOXB4, were found to be significantly overexpressed in venetoclax sensitive patients. Thus, these HOX-cluster genes expression biomarkers can be explored in a clinical trial setting to stratify AML patients responding to venetoclax based therapies. Study III, venetoclax treatment does not benefit all AML patients that demands identifying biomarkers to exclude the patients from venetoclax based therapies. The aim was to investigate transcriptomic biomarkers for ex vivo venetoclax resistance in AML patients. The correlation of ex vivo venetoclax response with gene expression profiles using a machine learning approach revealed significant overexpression of S100 family genes, S100A8 and S100A9. Moreover, high expression ofS100A9was found to be associated with birabresib (BET inhibitor) sensitivity. The overexpression of S100A8 and S100A9 could potentially be used to detect and monitor venetoclax resistance. The combination of BCL-2 and BET inhibitors may sensitize AML cells to venetoclax upon BET inhibition and block leukemic cell survival.