Indiana University-Purdue University Indianapolis (IUPUI) / Proteoforms are distinct protein molecule forms created by variations in genes, gene expression, and other biological processes. Many proteoforms contain multiple primary structural alterations, including amino acid substitutions, terminal truncations, and posttranslational modifications. These primary structural alterations play a crucial role in determining protein functions: proteoforms from the same protein with different alterations may exhibit different functional behaviors. Because top-down mass spectrometry directly analyzes intact proteoforms and provides complete sequence information of proteoforms, it has become the method of choice for the identification of complex proteoforms. Although instruments and experimental protocols for top-down mass spectrometry have been advancing rapidly in the past several years, many computational problems in this area remain unsolved, and the development of software tools for analyzing such data is still at its very early stage. In this dissertation, we propose several novel algorithms for challenging computational problems in proteoform identification by top-down mass spectrometry. First, we present two approximate spectrum-based protein sequence filtering algorithms that quickly find a small number of candidate proteins from a large proteome database for a query mass spectrum. Second, we describe mass graph-based alignment algorithms that efficiently identify proteoforms with variable post-translational modifications and/or terminal truncations. Third, we propose a Markov chain Monte Carlo method for estimating the statistical signi ficance of identified proteoform spectrum matches. They are the first efficient algorithms that take into account three types of alterations: variable post-translational modifications, unexpected alterations, and terminal truncations in proteoform identification. As a result, they are more sensitive and powerful than other existing methods that consider only one or two of the three types of alterations. All the proposed algorithms have been incorporated into TopMG, a complete software pipeline for complex proteoform identification. Experimental results showed that TopMG significantly increases the number of identifications than other existing methods in proteome-level top-down mass spectrometry studies. TopMG will facilitate the applications of top-down mass spectrometry in many areas, such as the identification and quantification of clinically relevant proteoforms and the discovery of new proteoform biomarkers. / 2019-06-21

abstract: In oxygenic photosynthesis, Photosystem I (PSI) and Photosystem II (PSII) are two transmembrane protein complexes that catalyze the main step of energy conversion; the light induced charge separation that drives an electron transfer reaction across the thylakoid membrane. Current knowledge of the structure of PSI and PSII is based on three structures: PSI and PSII from the thermophilic cyanobacterium Thermosynechococcus elonagatus and the PSI/light harvesting complex I (PSI-LHCI) of the plant, Pisum sativum. To improve the knowledge of these important membrane protein complexes from a wider spectrum of photosynthetic organisms, photosynthetic apparatus of the thermo-acidophilic red alga, Galdieria sulphuraria and the green alga, Chlamydomonas reinhardtii were studied. Galdieria sulphuraria grows in extreme habitats such as hot sulfur springs with pH values from 0 to 4 and temperatures up to 56°C. In this study, both membrane protein complexes, PSI and PSII were isolated from this organism and characterized. Ultra-fast fluorescence spectroscopy and electron microscopy studies of PSI-LHCI supercomplexes illustrate how this organism has adapted to low light environmental conditions by tightly coupling PSI and LHC, which have not been observed in any organism so far. This result highlights the importance of structure-function relationships in different ecosystems. Galdieria sulphuraria PSII was used as a model protein to show the amenability of integral membrane proteins to top-down mass spectrometry. G.sulphuraria PSII has been characterized with unprecedented detail with identification of post translational modification of all the PSII subunits. This study is a technology advancement paving the way for the usage of top-down mass spectrometry for characterization of other large integral membrane proteins. The green alga, Chlamydomonas reinhardtii is widely used as a model for eukaryotic photosynthesis and results from this organism can be extrapolated to other eukaryotes, especially agricultural crops. Structural and functional studies on the PSI-LHCI complex of C.reinhardtii grown under high salt conditions were studied using ultra-fast fluorescence spectroscopy, circular dichroism and MALDI-TOF. Results revealed that pigment-pigment interactions in light harvesting complexes are disrupted and the acceptor side (ferredoxin docking side) is damaged under high salt conditions. / Dissertation/Thesis / Ph.D. Biochemistry 2010

La spectrométrie de masse, initialement développée pour de petites molécules, a permis au cours de la dernière écoulée d’étudier en phase gazeuse des assemblages macro-moléculaires intacts, posant nombre de questions algorithmiques difficiles, dont trois sont étudiées dans cette thèse. La première contribution concerne la détermination de stoichiométrie (SD), et vise à trouver le nombre de copies de chaque constituant dans un assemblage. On étudie le cas où la masse cible se trouve dans un intervalle dont les bornes rendent compte des incertitudes des mesures des masses. Nous présentons un algorithme de taille mémoire constante (DIOPHANTINE), et un algorithme de complexité sensible à la sortie (DP++), plus performants que l’état de l’art, pour des masses en nombre entier ou flottant. La seconde contribution traite de l’inférence de connectivité à partir d’une liste d’oligomères dont la composition en termes de sous-unités est connue. On introduit le problème d’inférence de connectivité minimale (MCI) et présente deux algorithmes pour le résoudre. On montre aussi un accord excellent entre les contacts trouvés et ceux détermines expérimentalement. La troisième contribution aborde le problème d’inférence de connectivité de poids minimal, lorsque chaque contact potentiel a un poids reflétant sa probabilité d’occurrence. On présente en particulier un algorithme de bootstrap permettant de trouver un ensemble d’arêtes de sensitivité et spécificité meilleures que celles obtenues pour les solutions du problème MCI. / Mass spectrometry (MS), an analytical technique initially invented to deal with small molecules, has emerged over the past decade as a key approach in structural biology. The recent advances have made it possible to transfer large macromolecular assemblies into the vacuum without their dissociation, raising challenging algorithmic problems. This thesis makes contributions to three such problems. The first contribution deals with stoichiometry determination (SD), namely the problem of determining the number of copies of each subunit of an assembly, from mass measurements. We deal with the interval SD problem, where the target mass belongs to an interval accounting for mass measurement uncertainties. We present a constant memory space algorithm (DIOPHANTINE), and an output sensitive dynamic programming based algorithm (DP++), outperforming state-of-the-art methods both for integer type and float type problems. The second contribution deals with the inference of pairwise contacts between subunits, using a list of sub-complexes whose composition is known. We introduce the Minimum Connectivity Inference problem (MCI) and present two algorithms solving it. We also show an excellent agreement between the contacts reported by these algorithms and those determined experimentally. The third contribution deals with Minimum Weight Connectivity Inference (MWCI), a problem where weights on candidate edges are available, reflecting their likelihood. We present in particular a bootstrap algorithm allowing one to report a set of edges with improved sensitivity and specificity with respect to those obtaining upon solving MCI.