Development of NMR methods to study disordered proteins

In the field of bioscience there is an ongoing explosive growth in discovery and information. Novel means in biotechnology as well as in medicines are introduced at an unseen rate. One of the aspects contributing to this development is the increased understanding of protein function and structure. Proteins have a role in almost every biological process. The function and structure of proteins are linked. Recent studies have discovered that the understanding of the protein structure has been biased. Namely, the studies have unearthed a previously dismissed protein structure state: intrinsically disordered proteins (IDPs). In this highly dynamic state a protein is without a globular fold, but does not meet the requirements of a random coil either. Rapid transition between folds renders most of the established research techniques to be poor methods to study the IDPs. Nuclear magnetic resonance (NMR) is a spectroscopy method, which enables the study of molecules at atomic resolution. The technique is based upon manipulation of the nuclear spins in specifically produced sample under strong magnetic field. In this method, spins of the system generate quantum coherence state(s), which is utilized to obtain information about the system. NMR is suitable for studying samples in solid and liquid mediums, but in case of biomolecules, water solution is preferable as it resembles in vivo environment. Highly mobile structure and chemical composition of IDPs cause many established NMR experiments to fail. Development of NMR pulse sequences is an obvious approach to solve the problem. This thesis presents a number of NMR pulse sequences, which are designed to improve acquisition of information from highly mobile sections of proteins. The key aspect is to utilize H atom instead of HN in coherence transfer. Additional improvements include limited residue specific identification and novel coherence transfer pathways. Articles I, II, and III present triple resonance experiments, which correlate protein backbone atoms. Combination of the spectra enables full sequential assignment. Article IV introduces an improved pulse sequence for measuring J couplings between nitrogen and amide proton. The experiments were subjected to experimental verification. Comparisons were drawn between established pulse sequences. In both globular proteins and IDPs the results show improvement over established pulse sequences. The proposed sequences yielded improved assignment coverage, resolution and sensitivity enhancement.Biotieteiden alalla on käynnissä räjähdysmäinen kehitys. Uusia tutkimusmetodeja ja tuloksia julkaistaan ennennäkemättömällä tahdilla. Yksi tämän kehityksen mahdollistava tekijä on ymmärrys proteiinien rakenteesta ja toiminnasta. Proteiineilla on merkittävä rooli miltei kaikissa bio-prosesseissa. Proteiinien rakenteen muutoksilla on merkittävä rooli niiden toiminnassa. Viimeaikaiset tutkimukset ovat osoittaneet, että käsitys proteiinien rakenteesta on ollut puutteellinen. Rakenteellisen ja rakenteettomien tilojen välillä esiintyvä ns. intrinsically disordered proteiinit (IDP) esiintyvät dynaamisessa muodossa. Tämän tilan tutkiminen vakiintuneilla metodeilla on vaikeaa. Ydinmagneettinen resonanssi (NMR) mahdollistaa molekyylien tutkimisen atomaarisella resoluutiolla. Tekniikka perustuu ydinspinin manipulaatioon voimakkaassa magneettikentässä. Spinit saatetaan kvanttikoherenssitilaan, joita observoimalla voidaan systeemistä saada tietoa. Metodi soveltuu dynaamisten systeemien tutkimiseen. Tämä tekee NMR:stä hyvän tekniikan IDP:n tutkimiseen. Kuitenkin vakiintuneet NMR:n metodit eivät suoraan sovellut IDP:n tutkimiseen. Väitöskirjassa esitellään muuteltuja ja paranneltuja NMR pulssisarjoja, jotka soveltuvat paremmin IDP:n tutkimiseen

Screening for potential undiagnosed Gaucher disease patients : Utilisation of the Gaucher earlier diagnosis consensus point-scoring system (GED-C PSS) in conjunction with electronic health record data, tissue specimens, and small nucleotide polymorphism (SNP) genotype data available in Finnish biobanks

Background: Autosomal recessive Gaucher disease (GD) is likely underdiagnosed in many countries. Because the number of diagnosed GD patients in Finland is relatively low, and the true prevalence is currently not known, it was hypothesized that undiagnosed GD patients may exist in Finland. Our previous study demonstrated the applicability of Gaucher Earlier Diagnosis Consensus point-scoring system (GED-C PSS; Mehta et al., 2019) and Finnish biobank data and specimens in the automated point scoring of large populations. An indicative point -score range for Finnish GD patients was determined, but undiagnosed patients were not identified partly due to high number of high-score subjects in combination with a lack of suitable samples for diagnostics in the assessed biobank population. The current study extended the screening to another biobank and evaluated the feasibility of utilising the automated GED-C PSS in conjunction with small nucleotide polymorphism (SNP) chip genotype data from the FinnGen study of biobank sample donors in the identification of undiagnosed GD patients in Finland. Furthermore, the applicability of FFPE tissues and DNA restoration in the next-generation sequencing (NGS) of the GBA gene were tested. Methods: Previously diagnosed Finnish GD patients eligible to the study, and up to 45,100 sample donors in Helsinki Biobank (HBB) were point scored. The GED-C point scoring, adjusted to local data, was automated, but also partly manually verified for GD patients. The SNP chip genotype data for rare GBA variants was visually assessed. FFPE tissues of GD patients were obtained from HBB and Biobank Borealis of Northern Finland (BB). Results: Three previously diagnosed GD patients and one patient previously treated for GD-related features were included. A genetic diagnosis was confirmed for the patient treated for GD-related features. The GED-C point score of the GD patients was 12.5-22.5 in the current study. The score in eight Finnish GD patients of the previous and the current study is thus 6-22.5 points per patient. In the automated point scoring of the HBBPeer reviewe

Use of electronic health record data mining for heart failure subtyping

Abstract Objective To assess whether electronic health record (EHR) data text mining can be used to improve register-based heart failure (HF) subtyping. EHR data of 43,405 individuals from two Finnish hospital biobanks were mined for unstructured text mentions of ejection fraction (EF) and validated against clinical assessment in two sets of 100 randomly selected individuals. Structured laboratory data was then incorporated for a categorization by HF subtype (HF with mildly reduced EF, HFmrEF; HF with preserved EF, HFpEF; HF with reduced EF, HFrEF; and no HF). Results In 86% of the cases, the algorithm-identified EF belonged to the correct HF subtype range. Sensitivity, specificity, PPV and NPV of the algorithm were 94–100% for HFrEF, 85–100% for HFmrEF, and 96%, 67%, 53% and 98% for HFpEF. Survival analyses using the traditional diagnosis of HF were in concordance with the algorithm-based ones. Compared to healthy individuals, mortality increased from HFmrEF (hazard ratio [HR], 1.91; 95% confidence interval [CI], 1.24–2.95) to HFpEF (2.28; 1.80–2.88) to HFrEF group (2.63; 1.97–3.50) over a follow-up of 1.5 years. We conclude that quantitative EF data can be efficiently extracted from EHRs and used with laboratory data to subtype HF with reasonable accuracy, especially for HFrEF

Conformational Characterization of Intrinsically Disordered Proteins and Its Biological Significance

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