Nikolas Pontikos

Nikolas Pontikos

London, England, United Kingdom
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About

Associate Professor at University College London Institute of Ophthalmology working at…

Articles by Nikolas

  • Digital Opportunities 2023
    Dec 24, 2023

    Digital Opportunities 2023

    Taking a moment out from watching Die Hard to remember our Digital Opportunities module at the UCL Bioscience…

    3 Comments

Activity

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Experience

  • UCL Institute of Ophthalmology Graphic

    UCL Institute of Ophthalmology

    London, England, United Kingdom

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    United Kingdom

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    Institute of Ophthalmology, University College London

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    London, England, United Kingdom

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    London, United Kingdom

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    London, United Kingdom

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    London

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    London, United Kingdom

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    London, United Kingdom

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    London, United Kingdom

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    Cambridge, United Kingdom

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    London, United Kingdom

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    London, United Kingdom

Education

  • University of Cambridge Graphic

    Cambridge University

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    My PhD research was primarily on the development of data analysis techniques in high-throughput flow cytometry for characterising the immune profile associated with type 1 diabetes.
    I have also worked on some genetic data, in particular correlating qPCR and SNP signals to impute copy number variation in type 1 diabetes candidate genes.

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    Masters in bioinformatics to transition into the world of biology from computer science.

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    Activities and Societies: techsoc co-founder, techsoc football captain (from bottom of grassroot league to winner under my captainship ;))

    First exposure to object-oriented programming, through Java but also self-taught Perl and Python. Learned about computer internals and compiler design.

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    Activities and Societies: Skateboarding and Kung-fu :)

    Programming on TI-83 :)

Licenses & Certifications

Publications

  • Autosomal-Dominant Corneal Endothelial Dystrophies CHED1 and PPCD1 Are Allelic Disorders Caused by Non-coding Mutations in the Promoter of OVOL2.

    American Journal of Human Genetics

    Congenital hereditary endothelial dystrophy 1 (CHED1) and posterior polymorphous corneal dystrophy 1 (PPCD1) are autosomal-dominant corneal endothelial dystrophies that have been genetically mapped to overlapping loci on the short arm of chromosome 20. We combined genetic and genomic approaches to identify the cause of disease in extensive pedigrees comprising over 100 affected individuals. After exclusion of pathogenic coding, splice-site, and copy-number variations, a parallel approach using…

    Congenital hereditary endothelial dystrophy 1 (CHED1) and posterior polymorphous corneal dystrophy 1 (PPCD1) are autosomal-dominant corneal endothelial dystrophies that have been genetically mapped to overlapping loci on the short arm of chromosome 20. We combined genetic and genomic approaches to identify the cause of disease in extensive pedigrees comprising over 100 affected individuals. After exclusion of pathogenic coding, splice-site, and copy-number variations, a parallel approach using targeted and whole-genome sequencing facilitated the identification of pathogenic variants in a conserved region of the OVOL2 proximal promoter sequence in the index families (c.-339_361dup for CHED1 and c.-370T>C for PPCD1). Direct sequencing of the OVOL2 promoter in other unrelated affected individuals identified two additional mutations within the conserved proximal promoter sequence (c.-274T>G and c.-307T>C). OVOL2 encodes ovo-like zinc finger 2, a C2H2 zinc-finger transcription factor that regulates mesenchymal-to-epithelial transition and acts as a direct transcriptional repressor of the established PPCD-associated gene ZEB1. Interestingly, we did not detect OVOL2 expression in the normal corneal endothelium. Our in vitro data demonstrate that all four mutated OVOL2 promoters exhibited more transcriptional activity than the corresponding wild-type promoter, and we postulate that the mutations identified create cryptic cis-acting regulatory sequence binding sites that drive aberrant OVOL2 expression during endothelial cell development. Our data establish CHED1 and PPCD1 as allelic conditions and show that CHED1 represents the extreme of what can be considered a disease spectrum. They also implicate transcriptional dysregulation of OVOL2 as a common cause of dominantly inherited corneal endothelial dystrophies.

    Other authors
    See publication

  • Dissection of a Complex Disease Susceptibility Region Using a Bayesian Stochastic Search Approach to Fine Mapping

    PLOS Genetics

    Other authors
    See publication

  • A hybrid qPCR/SNP array approach allows cost efficient assessment of KIR gene copy numbers in large samples

    BMC Genomics

    Other authors
    See publication

  • UniProt Knowledgebase: a hub of integrated protein data

    Database : the journal of biological databases and curation

    Just the yearly Uniprot publication and I am in the list of authors since I was working there at the time.

    See publication

Projects

  • Association of KIR with T1D

    - Present

    Killer Immunoglobulin-like Receptors (KIR) play an important role in the innate immune system. Present on the surface of Natural Killer cells, KIRs mediate the fate of target cells based on the composite inhibiting/activating signal generated by binding to their HLA Class I ligands. Type 1 Diabetes (T1D) is an autoimmune disease known to be strongly associated with the HLA region, primarily with HLA Class II genes, but also with HLA Class I loci, such as HLA-Bw4/Bw6 epitope (P=6.57E-6…

    Killer Immunoglobulin-like Receptors (KIR) play an important role in the innate immune system. Present on the surface of Natural Killer cells, KIRs mediate the fate of target cells based on the composite inhibiting/activating signal generated by binding to their HLA Class I ligands. Type 1 Diabetes (T1D) is an autoimmune disease known to be strongly associated with the HLA region, primarily with HLA Class II genes, but also with HLA Class I loci, such as HLA-Bw4/Bw6 epitope (P=6.57E-6 conditional on HLA Class II). Of the 17 known KIR genes, KIR3DL1 is the only one known to interact biologically with HLA-Bw4, which makes it a suitable candidate gene for T1D. Furthermore, its activating counterpart, KIR3DS1, may also putatively interact with HLA-Bw4. We conducted a case-control study (816 cases: 813 controls) to assess whether there is evidence that copy number variation in KIR3DL1/3DS1 is associated with T1D.

    See project

  • Data Analysis in Flow Cytometry

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    My PhD research is primarily on the development of data analysis techniques in high-throughput flow cytometry for characterising the immune profile associated with type 1 diabetes, and more generally on unsupervised and supervised clustering methods.

    See project

  • flowBeads Bioconductor package

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    A software package I wrote as part of my PhD to automate the analysis of bead data used for the purpose of normalisation in flow cytometry.

    See project

  • Association of CD25 expression with IL2RA genotype

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    I started off my PhD by reanalysing, using computational methods (k-means, mixtures of univariate distributions), previous published data to test the correlation between CD25 expression on naive and memory T cells with regulating SNPs in the IL2RA gene. I found that automatic methods were able to outdo manual methods by improving the reproducibility of the results and the strength of the correlation but did poorly when the data did not fit the prior assumptions (e.g. number of clusters larger…

    I started off my PhD by reanalysing, using computational methods (k-means, mixtures of univariate distributions), previous published data to test the correlation between CD25 expression on naive and memory T cells with regulating SNPs in the IL2RA gene. I found that automatic methods were able to outdo manual methods by improving the reproducibility of the results and the strength of the correlation but did poorly when the data did not fit the prior assumptions (e.g. number of clusters larger than expected). But this seeming weakness of the automatic method is in fact one of its strength as it makes for an excellent outlier detection tool, capabale of spotting cases were the data does not fit the expected model. I summarised and presented some of my findings as a poster (18-06-2012) at the Cyto 2012 Conference in Leipzig.

    See project

  • Identification of PML Bodies in CLSM Images

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    Processing 3D nuclei images obtained from a Confocal Laser Scanning Microscopy (CLSM). In particular fine-tuning the Stable Count Thresholding algorithm for identifying fluorescently stained promyelotic (PML) nuclear bodies in cells which have undergone heat-shock treatment.
    - Technologies: R, various Bioconductor packages, C and Python

  • Copy Number Variation in Breast Cancer

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    Data analysis project involving DNA Copy Number Variations (CNV) profiling in genome-wide data obtained from BAC32K and Illumina HumanCNV370 BeadChip array-comparative genomic hybridisation experiments performed on 26 breast cancer cell lines. Different CNV calling methods such as a heuristic threshold and a hidden Markov model approach were compared.
    - Technologies: Python, R and various R packages in Bioconductor

    Other creators

  • KinomePhosphatome Database

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    Group project in a team of four during which we created a database with a front-end website for kinases, phosphatases, the corresponding substrates as well as the reactions and pathways in which they are involved. We also gathered evolutionary information about kinase and phosphatase protein families. We successfully integrated and unified many data sources such as Uniprot, PhosphoELM, NetworKIN, Phosida, PhosphoPOINT, Reactome, Panther, KEGG, dbPTM and Treefam.
    - Technologies: Python…

    Group project in a team of four during which we created a database with a front-end website for kinases, phosphatases, the corresponding substrates as well as the reactions and pathways in which they are involved. We also gathered evolutionary information about kinase and phosphatase protein families. We successfully integrated and unified many data sources such as Uniprot, PhosphoELM, NetworKIN, Phosida, PhosphoPOINT, Reactome, Panther, KEGG, dbPTM and Treefam.
    - Technologies: Python, MySQL, Ajax, Django-Python

    Other creators
    See project

  • Wireless sensor network routing

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    Final year project on loss-aware forwarding in Greedy Perimeter Stateless Routing (GPSR) for wireless sensor networks. Gathered loss measurement data over long periods of time on a 40-node wireless sensor network and derived statistical properties of loss. Have improved performance of GPSR for certain topologies in terms of end-to-end delay and power usage by reducing retransmission count.
    - Technologies: NesC, TinyOS, TOSSIM, Msp430 toolchain, C, Perl, Python,
    Gnuplot

  • Assisted Testing Environment

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    Group project involving the design and implementation of a test specification
    language to generate unit tests, as well as a graphical interface to assist in the creation and execution of these tests. The specification language was parsed into an XML abstract syntax tree from which, an XSLT processor was used to generate either TestNG code or JUnit code. Our project won the first prize at the Goldman Sachs group presentation.
    - Technologies: Java, Ant, JavaCUP, TestNG, XML and XSLT

    Other creators
    See project

  • Hospital System

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    Three-tier Hospital System coursework featuring a client, a login server and a patient record server. System needed to support many users, allowing them to concurrently read/write the same patient record.
    - Technologies: Java, Ant, threads, non-blocking sockets, RMI, XML, JAXB

    Other creators

  • Spaceship Game

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    Side-scrolling spaceship game implemented in Java. Main features include parallax scrolling, rule-based enemy AI and collision detection.

    See project

Languages

  • English

    Native or bilingual proficiency

  • French

    Native or bilingual proficiency

  • Greek

    Limited working proficiency

  • German

    Elementary proficiency

Organizations

  • British Computer Society and Chartered Institute for IT

    Fellow

    - Present

  • British Computer Society and Chartered Institute for IT

    Fellow

    - Present

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