Early Folding Biases in the Folding Free-Energy Surface of βα-Repeat Proteins: A Dissertation

Early events in folding can determine if a protein is going to fold, misfold, or aggregate. Understanding these deterministic events is paramount for de novo protein engineering, the enhancement of biopharmaceutical stabilities, and understanding neurodegenerative diseases including amyotrophic lateral sclerosis and Alzheimer\u27s disease. However, the physicochemical and structural biases within high energy states of protein biopolymers are poorly understood. A combined experimental and computational study was conducted on the small β/α-repeat protein CheY to determine the structural basis of its submillisecond misfolding reaction to an off-pathway intermediate. Using permutations, we were able to discriminate between the roles of two proposed mechanisms of folding; a nucleation condensation model, and a hydrophobic collapse model driven by the formation of clusters of isoleucine, leucine, and valine (ILV) residues. We found that by altering the ILV cluster connectivity we could bias the early folding events to either favor on or off-pathway intermediates. Structural biases were also experimentally observed in the unfolded state of a de novo designed synthetic β/α-repeat protein, Di-III_14. Although thermodynamically and kinetically 2-state, Di-III_14 has a well structured unfolded state that is only observable under native-favoring conditions. This unfolded state appears to retain native-like structure, consisting of a hydrophobic 7 core (69% ILV) stabilized by solvent exposed polar groups and long range electrostatic interactions. Together, these results suggest that early folding events are largely deterministic in these two systems. Generally, low contact order ILV clusters favor local compaction and, in specific cases, long range electrostatic interactions may have stabilizing effects in higher energy states

Unraveling Binding Effects of Cobalt(II) Sepulchrate with the Monooxygenase P450 BM-3 Heme Domain Using Molecular Dynamics Simulations

One of the major limitations to exploit enzymes in industrial processes is their dependence on expensive reduction equivalents like NADPH to drive their catalytic cycle. Soluble electron transfer (ET) mediators like Cobalt(II)Sepulchrate have been proposed as a cost-effective alternative to shuttle electrons between an inexpensive electron source and enzyme redox center. The interactions of these molecules with enzymes are not elucidated at molecular level yet. Herein, molecular dynamics simulations are performed to understand the binding and ET mechanism of the Cobalt(II)Sepulchrate with the heme domain of cytochrome P450BM-3. The study provides a detailed map of ET mediator binding sites on protein surface that resulted prevalently composed by Asp and Glu amino acids. The Cobalt(II)Sepulchrate do not show a preferential binding to these sites. However, among the observed binding sites, only few of them provide efficient ET pathways to heme iron. The results of this study can be used to improve the ET mediator efficiency of the enzyme for possible biotechnological applications

Minkowski Tensors of Anisotropic Spatial Structure

This article describes the theoretical foundation of and explicit algorithms for a novel approach to morphology and anisotropy analysis of complex spatial structure using tensor-valued Minkowski functionals, the so-called Minkowski tensors. Minkowski tensors are generalisations of the well-known scalar Minkowski functionals and are explicitly sensitive to anisotropic aspects of morphology, relevant for example for elastic moduli or permeability of microstructured materials. Here we derive explicit linear-time algorithms to compute these tensorial measures for three-dimensional shapes. These apply to representations of any object that can be represented by a triangulation of its bounding surface; their application is illustrated for the polyhedral Voronoi cellular complexes of jammed sphere configurations, and for triangulations of a biopolymer fibre network obtained by confocal microscopy. The article further bridges the substantial notational and conceptual gap between the different but equivalent approaches to scalar or tensorial Minkowski functionals in mathematics and in physics, hence making the mathematical measure theoretic method more readily accessible for future application in the physical sciences

Comparative Evaluation of Methods for Sequence Alignment and Annotation

The speed of DNA and RNA sequencing has long ago surpassed the capacity of laboratories to assign function to these sequences by direct experiment. Fortunately, function and other information can be effectively transferred to novel data from previously accumulated knowledge by sequence homology. This has resulted in the development of hundreds of novel homology-based methods. However, the tendency of method developers to be overoptimistic about their own results, biases in the evaluation metrics used to rank methods, inconsistency between different rankings and evaluation metrics, misplaced popularity of methods relative to their performance all indicate that, in many cases, clear knowledge of the comparative performance of different methods is lacking. This has two main consequences. First, researchers use suboptimal tools. Second, method development may go astray because the merits used for guiding method optimization are biased or unclear. To avoid these difficulties, further research is needed into methodology of evaluation and comparative studies. One core approach for transferring function by sequence homology is to create a multiple sequence alignment (MSA) that represents a given group of similar sequences. The resulting alignment can be applied to annotate novel sequences using profile hidden Markov models (HMMs), to create phylogenetic trees or to compare structural features. The application of MSAs and profile HMMs for genome annotation was explored in publication (I). Creating MSA has been addressed by a vast field of research, however there is a lack of independent comparative studies and no comparative studies for alignment strategies. In publication (II) a novel modular MSA aligner was implemented to aid in comparative evaluation of different MSA strategies. Different MSA strategies were then compared to each other and to the state-of-the-art MSA software on three benchmark databases. Another core approach has been to combine homology searches with assignment of annotation terms from a controlled vocabulary such as the Gene Ontology (GO). Hundreds of methods that assign GO terms to novel sequences have been introduced. The research community has also invested into the objective evaluation of these methods via third party competitions. However, the evaluation metrics and merits used in these competitions are still under active debate and need further research and development. In publication (III) a novel framework was introduced for the development of unbiased high-quality evaluation metrics. By testing 37 variations of popular metrics, our approach revealed strong differences between metrics, a list of clearly biased metrics, and a list of high-quality metrics that are well suited for the evaluation of GO annotations. In summary, this thesis presents novel frameworks and implementation platforms for comparative evaluation of two important classes of homology-based methods: MSA aligners and GO sequence classifiers. These results will be instrumental for developing more accurate MSA aligners, for eliminating many forms of bias inherent in contemporary evaluation protocols, for producing informative method rankings for non-specialist users and for guiding method development towards merits that truly reflect the utility of the designed tools.Johtuen DNA ja RNA sekvensointiteknologian nopeasta kehityksestä suurin osa sekvenssien biologisista kuvauksista tuotetaan sekvenssihomologiaan perustuvilla automaattisilla menetelmillä. Homologiaan perustuvia menetelmiä on kehitetty satoja, mikä korostaa objektiivisen ja riippumattoman menetelmävertailun merkitystä. On monia virhelähteitä, jotka vääristävät ja hankaloittavat menetelmävertailua: oman menetelmän yliarviointi, ylisovittaminen, valikoitu raportointi, sekä harhaiset ja keskenään ristiriitaiset arviointimetriikat. Harhaisella menetelmävertailulla on kaksi merkittävää seurausta: (1) epäoptimaaliset menetelmät päätyvät tutkijayhteisön käyttöön, (2) menetelmäkehitys harhaantuu, koska kehitystä ohjaavat arviointikriteerit ovat harhaisia tai epäselviä. Edellä mainittuja vaikeuksia voidaan välttää kohdentamalla tutkimusta itse vertailevaan menetelmäarviointiin. Monisekvenssilinjaus (MSL) on sekvenssihomologiaan perustuva menetelmä, jolla on hyvin laaja sovelluskenttä molekyylibiologisessa tutkimustyössä. Julkaisussa (I) tutkittiin MSL-linjausten ja Markovin piilomallien soveltamista bakteerigenomien kuvaukseen. MSL-kentällä on edelleen puutetta riippumattomasta menetelmäarvioinnista, ja erityisesti eri MSL-algoritmiratkaisuja vertailevista tutkimuksista. Julkaisussa (II) esitettiin uusi modulaarinen MSL-ohjelma, jonka avulla useita MSL-algoritmiratkaisuja vertailtiin toisiinsa ja MSL-alan huippusovelluksiin kolmella vertailutietokannalla. Vertailun perusteella annettiin selkeitä suosituksia optimaalisista MSL-algoritmiratkaisuista ja parhaista MSL-ohjelmista. Sekvenssikuvauksia tuottavat automaattiset menetelmät useimmiten käyttävät geeniontologian (GO) termistöä. Koska vuosittain julkaistaan satoja GO-menetelmiä, tutkimusyhteisö on panostanut kyseisten menetelmien vertailevaan arviointiin. Kuitenkin GO-menetelmävertailun kentällä arviointikriteerit ovat vakiintumattomia ja monet käytössä olevat arviointimetriikat ovat joko harhaisia tai keskenään ristiriitaisia. Julkaisussa (III) ehdotetaan ratkaisuksi uutta menetelmää, jonka avulla on mahdollista testata ja kehittää korkealaatuisia ja harhattomia arviointimetriikoita. Julkaisussa (III) testattiin useita arviointimetriikoita ja osoitettiin, että monet tällä hetkellä käytössä olevat GO-arviointimetriikat ovat voimakkaasti harhaisia. Testauksen perusteella annettiin myös selkeitä suosituksia arviointimetriikoista, jotka takaavat harhattoman menetelmävertailun

Bacterial diversity within and outside the premises of a South Norwegian salmon fish farm

Master's thesis in Coastal ecology (BIO501)Norwegian salmon farming is a rapidly expanding sector and the Norwegian Government have a set goal to facilitate a five-fold growth towards 2050. Organic enrichment of the surrounding waters and the sediment below the cages due to the inputs of organic matter from uneaten food, tissue and faecal matter etc., affect the macro -and microfauna. To monitor the effect of these organic inputs, fish breeding companies must perform periodic controls. Traditionally, these periodic controls are based on time-consuming and expensive methods, and the necessary taxonomic knowledge is declining. In this study, we evaluated the usefulness of marine bacterial communities as bioindicators. Benthic samples were collected from within the premises of a fish breeding facility and compared with samples from outside the facility based on metabarcoding of the 16S rRNA gene. Water samples were also collected from the same sites, and from different depths representing different water layers. The bacterioplankton composition in both benthic and water samples showed significant shifts from within the facility compared to stations outside the fish farm. The bacterial composition also varied greatly between the different water layers. Our results demonstrate the potential for bacterioplankton composition diversity as bioindicators, and that this methodology could be a useful asset in the periodic monitoring controls

Targeted and Genome-Scale Methylomics Reveals Gene Body Signatures in Human Cell Lines

Cytosine methylation, an epigenetic modification of DNA, is a target of growing interest for developing high throughput profiling technologies. Here we introduce two new, complementary techniques for cytosine methylation profiling utilizing next generation sequencing technology: bisulfite padlock probes (BSPPs) and methyl sensitive cut counting (MSCC). In the first method, we designed a set of ~10,000 BSPPs distributed over the ENCODE pilot project regions to take advantage of existing expression and chromatin immunoprecipitation data. We observed a pattern of low promoter methylation coupled with high gene body methylation in highly expressed genes. Using the second method, MSCC, we gathered genome-scale data for 1.4 million HpaII sites and confirmed that gene body methylation in highly expressed genes is a consistent phenomenon over the entire genome. Our observations highlight the usefulness of techniques which are not inherently or intentionally biased in favor of only profiling particular subsets like CpG islands or promoter regions

Safe and Complete Algorithms for Dynamic Programming Problems, with an Application to RNA Folding

Peer reviewe

Engineering solid-state nanopores for detection of single transcription factors bound to DNA

Thesis (Ph.D.)--Boston UniversityDetection and characterization of nucleic acid-protein interactions, particularly those involving DNA and transcription factors, remain significant barriers to our understanding of genetic regulation. Solid-state nanopores are extremely sensitive single molecule sensors with the capability to map local chemical and structural characteristics along the length of a biopolymer, providing label-free detection for a wide range of analyte lengths and sizes. Previous studies have utilized solid-state nanopores to detect complexes of DNA bound to many large proteins, but improvements to the sensing resolution of the nanopore platform are necessary for detection of single small transcription factors bound to DNA. This project encompasses two novel nanopore modifications that enhance output signal quality and time resolution in nanopores, and establishes solid-state nanopores as a platform for direct measurement of transcription factor-DNA complexes. First, a novel fabrication process was developed to create locally thinned SiN membranes on a full-wafer scale. These modified nanopore chips provide several advantages over conventional solid-state nanopores, including improved signal-to-background ratio, higher probability of functionality, and clearly marked pore locations for re-imaging and array fabrication. Next, the volume outside the nanopore was modified by electrospinning a sparse, hydrophobic co-polymer nanofiber mesh (NFM) directly onto the nanopore chip. The NFM interacts with analyte molecules as they translocate through the pore, increasing residence time in the sensing volume and improving resolution by more than two orders ofmagnitude for a chemically optimized blend ofpoly(E-caprolactone) and poly(glycerol-co-E-caprolactone). Finally, modified nanopores were used for direct, label-free detection of single transcription factors bound to DNA. Translocations of these complexes reveal a combination oftwo possible sensing modalities; either the complex passes unhindered through the pore, causing a transient drop in current at the location ofthe bound protein, or the protein is unable to translocate and is removed as the DNA is electrophoretically driven through the nanopore. The DNA-binding domain of the transcription factor Early Growth Response Protein 1 (EGRl), known as zif268, is presented as a model system for this research. EGRl activates genes that control cell differentiation and mitogenesis, and participates in many regulatory processes including wound response, tumor suppression, and neuronal plasticity