Robert Moulder
PhD, CChem, MRSC
robmou@utu.fi +358 29 450 3802 Tykistökatu 6 Turku Office: 7115 ORCID identifier: https://orcid.org/0000-0003-4742-0566 |
Areas of expertise
Chromatography, Mass spectrometry, proteomics, protein biomarkers, analytical chemistry, type 1 diabetes, T-helper cells, bioanalysis, supercritical fluids
Chromatography, Mass spectrometry, proteomics, protein biomarkers, analytical chemistry, type 1 diabetes, T-helper cells, bioanalysis, supercritical fluids
Biography
Following PhD studies at the University of Leeds on analytical applications of supercritical fluids, I combined these methodologies with mass spectrometry in biomarker research as a postdoctoral researcher at the Institute of Chemistry at Uppsala University, Sweden. From the chemistry department I moved to the Positron Emission Tomography facility at Uppsala University hospital where I worked as senior analytical chemist in a variety of projects including tracer quality control, development and metabolite analysis.
I moved to Finland to work with bioanalytics at Orion-Pharma, then back into academia at the University of Turku in the proteomics core facility at Turku Centre for Biotechnology. From the core facility I moved to the Molecular Immunology group of Professor Lahesmaa where I have used proteomics in the study of T helper cell subsets, in addition to biomarker studies of type 1 diabetes, sarcoidosis, atherosclerosis and ovarian cancer.
Following PhD studies at the University of Leeds on analytical applications of supercritical fluids, I combined these methodologies with mass spectrometry in biomarker research as a postdoctoral researcher at the Institute of Chemistry at Uppsala University, Sweden. From the chemistry department I moved to the Positron Emission Tomography facility at Uppsala University hospital where I worked as senior analytical chemist in a variety of projects including tracer quality control, development and metabolite analysis.
I moved to Finland to work with bioanalytics at Orion-Pharma, then back into academia at the University of Turku in the proteomics core facility at Turku Centre for Biotechnology. From the core facility I moved to the Molecular Immunology group of Professor Lahesmaa where I have used proteomics in the study of T helper cell subsets, in addition to biomarker studies of type 1 diabetes, sarcoidosis, atherosclerosis and ovarian cancer.
Research
With recent improvements in chromatographic and mass spectrometry technology it has been increasingly possible to provide detailed proteomic information of complex samples in a time efficient manner. Such characterizations of biological systems can provide important insight into cell biology and disease pathologies. Following this theme, my research pursuits are divided into two related categories, proteomic biomarker identification and proteomics characterization of cells pertinent to the immune system.
Using samples collected in the Finnish Diabetes Prediction and Prevention (DIPP) study I have used mass spectrometry based quantitative proteomics to identify early changes and risk related differences in the temporal proteomes of children that develop type 1 diabetes in comparison with age, gender and risk matched controls. Our publication of this research presented the first detailed temporal proteome of children at risk from T1D. Following on from this work further validations in independent cohorts are in progress, in addition to other T1D research and related studies. Similarly, using longitudinal samples we have studied the differences in the serum protein profiles of subjects with asymptomatic cardiovascular atherosclerosis.
The key genetic component for T1D is found amongst variants of the human leucocyte antigen (HLA) gene, the functions of which include activatation of CD4+ T cells. As inappropriate CD4+ T helper cell activation and polarization have been linked with several inflammatory and autoimmune diseases, an understanding of the molecular mechanisms of these processes is important in identifying the pathologies of related disease states. We have used quantitative proteomics to study the early changes in the differentiation process, including published proteomics works on Th17, Th2 and Th1 cells, including complementary genomics. Ongoing work concern the use of targeted and non-targeted proteomics to analyse these and other Th cell subsets, detailing protein interactions and temporal profiles.
With recent improvements in chromatographic and mass spectrometry technology it has been increasingly possible to provide detailed proteomic information of complex samples in a time efficient manner. Such characterizations of biological systems can provide important insight into cell biology and disease pathologies. Following this theme, my research pursuits are divided into two related categories, proteomic biomarker identification and proteomics characterization of cells pertinent to the immune system.
Using samples collected in the Finnish Diabetes Prediction and Prevention (DIPP) study I have used mass spectrometry based quantitative proteomics to identify early changes and risk related differences in the temporal proteomes of children that develop type 1 diabetes in comparison with age, gender and risk matched controls. Our publication of this research presented the first detailed temporal proteome of children at risk from T1D. Following on from this work further validations in independent cohorts are in progress, in addition to other T1D research and related studies. Similarly, using longitudinal samples we have studied the differences in the serum protein profiles of subjects with asymptomatic cardiovascular atherosclerosis.
The key genetic component for T1D is found amongst variants of the human leucocyte antigen (HLA) gene, the functions of which include activatation of CD4+ T cells. As inappropriate CD4+ T helper cell activation and polarization have been linked with several inflammatory and autoimmune diseases, an understanding of the molecular mechanisms of these processes is important in identifying the pathologies of related disease states. We have used quantitative proteomics to study the early changes in the differentiation process, including published proteomics works on Th17, Th2 and Th1 cells, including complementary genomics. Ongoing work concern the use of targeted and non-targeted proteomics to analyse these and other Th cell subsets, detailing protein interactions and temporal profiles.
Publications 
2 of 5
- Interactome Networks of FOSL1 and FOSL2 in Human Th17 Cells (2021)
- ACS Omega
(A1 Refereed original research article in a scientific journal) - CIP2A Constrains Th17 Differentiation by Modulating STAT3 Signaling (2020)
- iScience
(A1 Refereed original research article in a scientific journal) - Protein interactome of the Cancerous Inhibitor of Protein Phosphatase 2A (CIP2A) in Th17 cells (2020)
- Current Research in Immunology
(A1 Refereed original research article in a scientific journal) - Quantitative Proteomics Reveals the Dynamic Protein Landscape during Initiation of Human Th17 Cell Polarization (2019)
- iScience
(A1 Refereed original research article in a scientific journal) - Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling (2018)
- Mass Spectrometry Reviews
(A2 Refereed review article in a scientific journal ) - Characterization and non-parametric modeling of the developing serum proteome during infancy and early childhood (2018)
- Scientific Reports
(A1 Refereed original research article in a scientific journal) - Proteomics of Diabetes, Obesity, and Related Disorders (2018)
- PROTEOMICS - Clinical Applications
(B1 Non-refereed article in a scientific journal) - Quantitative proteomic characterization and comparison of T helper 17 and induced regulatory T cells (2018)
- PLoS Biology
(A1 Refereed original research article in a scientific journal) - Serum Proteomic Profiling to Identify Biomarkers of Premature Carotid Atherosclerosis (2018)
- Scientific Reports
(A1 Refereed original research article in a scientific journal) - DNA methylation and Transcriptome Changes Associated with Cisplatin Resistance in Ovarian Cancer (2017)
- Scientific Reports
(A1 Refereed original research article in a scientific journal)
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