Semiclassical Treatment of Interference Phenomena in Bosonic Quantum Many-Body Systems

A major goal of the semiclassical theory is to understand and treat a quantum system in the regime of large quantum numbers using information from its classical limit. In this framework, quantum phenomena are addressed through a path integral perspective, i.e. the weighted interference of phases accumulated along classical trajectories. While this formalism has been successful in explaining interference phenomena, for instance, in mesoscopic single-particle quantum systems, the recent extension of the semiclassical theory allows now also the treatment of interacting quantum many-body systems. This thesis aims to contribute to these ongoing efforts to apply semiclassical techniques to quantum many-body systems. It is focused on bosonic quantum many-body systems, where the thermodynamic limit of a large number of particles represents an alternative version of a semiclassical limit. Within the derivation of the corresponding semiclassical theory, mean-field equations, i.e. effective nonlinear wave equations describing the matter wave, re-emerge as Hamilton's equations of motion of an abstract Hamilton function, defining the above thermodynamic limit as the classical limit. Within this thesis, two different topics are studied. The first one deals with the so-called “Out-of-Time-Order Correlator” (OTOC), the expectation value of the squared commutator of two local operators at different times. The OTOC provides a direct probe for the presence of chaos in the classical limit (if any) of a quantum many-body system. This is based on that for short times the OTOC directly relates to the stability of classical solutions upon changes in their initial conditions. One of the defining properties of chaos is that this stability displays an exponential growth, with the rate called the classical Lyapunov exponent. Immediately, this implies an exponential growth of the OTOC for short times, from which the Lyapunov exponent can be extracted. For later times, one observes a saturation of the OTOC as a consequence of unitary quantum time evolution. The Ehrenfest time, the time scale which marks the onset of quantum interference, separates these different dynamical behaviors. In this thesis a thorough understanding of the concept of chaos in the classical limit of quantum many-body systems is provided, and with that the underlying interference mechanisms involved in the early exponential growth and the later saturation of OTOCs are identified. It is found that the pre-Ehrenfest time exponential growth is given through the interference of multiple contributions, all of them essentially following only a single solution of mean-field equations. Conversely the post-Ehrenfest time behavior stems from the contributions of fundamentally different mean-field solutions, which display correlated dynamics only for a limited amount of time, of the order of Ehrenfest time. The second topic covered in this thesis deals with the coherent transport of cold bosonic atoms through an Aharonov-Bohm ring structure. This setup consists of two semi-infinite wave guides attached on the opposite sides of a wave guide ring which is pierced by a synthetic gauge field. Within the ring, the atoms are further subject to both a weak disorder potential and particle-particle interaction. In the non-interacting case, the disorder-averaged transmission probability as a function of the encircled flux displays the well-known Al'tshuler-Aronov-Spivak (AAS) oscillations, i.e. oscillations with a frequency twice as large as Aharonov-Bohm oscillations. This thesis provides further insight into the influence of a weak particle-particle interaction on AAS oscillations, for which numerical results predict an interaction-based inversion of peaks. Here, using semiclassical techniques to solve the corresponding mean-field problem, this inversion is successfully reproduced, and a first indicator of the relevant mechanism leading to the inversion is found through contributions of self-averaging scattering path constellations

Protective Immunity Does Not Correlate with the Hierarchy of Virus-specific Cytotoxic T Cell Responses to Naturally Processed Peptides

Infection of C57BL/6 mice with lymphocytic choriomeningitis virus (LCMV) stimulates major histocompatibility complex class I–restricted cytotoxic T cells (CTLs), which normally resolve the infection. Three peptide epitopes derived from LCMV have been shown to bind the mouse class I molecule H-2 Db and to stimulate CTL responses in LCMV-infected mice. This report describes the identity and abundance of each CTL epitope after their elution from LCMV-infected cells. Based on this information, peptide abundance was found to correlate with the magnitude of each CTL response generated after infection with LCMV. Subsequent experiments, performed to determine the antiviral capacity of each CTL specificity, indicate that the quantitative hierarchy of CTL activity does not correlate with the ability to protect against LCMV infection. This report, therefore, indicates that immunodominant epitopes should be defined, not only by the strength of the CTL response that they stimulate, but also by the ability of the CTLs to protect against infection

Application of the pMHC array to characterise tumour antigen specific T cell populations in leukaemia patients at disease diagnosis

Immunotherapy treatments for cancer are becoming increasingly successful, however to further improve our understanding of the T-cell recognition involved in effective responses and to encourage moves towards the development of personalised treatments for leukaemia immunotherapy, precise antigenic targets in individual patients have been identified. Cellular arrays using peptide-MHC (pMHC) tetramers allow the simultaneous detection of different antigen specific T-cell populations naturally circulating in patients and normal donors. We have developed the pMHC array to detect CD8+ T-cell populations in leukaemia patients that recognise epitopes within viral antigens (cytomegalovirus (CMV) and influenza (Flu)) and leukaemia antigens (including Per Arnt Sim domain 1 (PASD1), MelanA, Wilms’ Tumour (WT1) and tyrosinase). We show that the pMHC array is at least as sensitive as flow cytometry and has the potential to rapidly identify more than 40 specific T-cell populations in a small sample of T-cells (0.8–1.4 x 106). Fourteen of the twenty-six acute myeloid leukaemia (AML) patients analysed had T cells that recognised tumour antigen epitopes, and eight of these recognised PASD1 epitopes. Other tumour epitopes recognised were MelanA (n = 3), tyrosinase (n = 3) and WT1126-134 (n = 1). One of the seven acute lymphocytic leukaemia (ALL) patients analysed had T cells that recognised the MUC1950-958 epitope. In the future the pMHC array may be used provide point of care T-cell analyses, predict patient response to conventional therapy and direct personalised immunotherapy for patients

Gapped sequence alignment using artificial neural networks: application to the MHC class I system

Motivation: Many biological processes are guided by receptor interactions with linear ligands of variable length. One such receptor is the MHC class I molecule. The length preferences vary depending on the MHC allele, but are generally limited to peptides of length 8–11 amino acids. On this relatively simple system, we developed a sequence alignment method based on artificial neural networks that allows insertions and deletions in the alignment. Results: We show that prediction methods based on alignments that include insertions and deletions have significantly higher performance than methods trained on peptides of single lengths. Also, we illustrate how the location of deletions can aid the interpretation of the modes of binding of the peptide-MHC, as in the case of long peptides bulging out of the MHC groove or protruding at either terminus. Finally, we demonstrate that the method can learn the length profile of different MHC molecules, and quantified the reduction of the experimental effort required to identify potential epitopes using our prediction algorithm. Availability and implementation: The NetMHC-4.0 method for the prediction of peptide-MHC class I binding affinity using gapped sequence alignment is publicly available at: http://www.cbs.dtu.dk/ services/NetMHC-4.0.Fil: Andreatta, Massimo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Nielsen, Morten. Technical University of Denmark; Dinamarca. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentin

Natural ligand motifs of H-2E molecules are allele specific and illustrate homology to HLA-DR molecules

Motifs of peptldes naturally associated with H-2Ek and Ed molecules were determined by (i) pool sequencing of natural ligand mixtures and (ii) sequencing of individual natural ligands followed by their alignment to the basic motif suggested by pool sequencing. The data reveal nine amino acid motifs with interaction sites at relative positions P1, P4, P6 and P9, with specificities that are identical at some but different at other anchor positions between Ed and Ek motifs, illustrating the different requirements for peptides to be presented by these two MHC molecules. The anchors with the most restricted specificity are P1 and P9. P1 is aliphatic for Ek and predominantly aromatic for Ed. P9 is positively charged for both molecules. P4 and P6 show a totally different amino acid preference between Ek and Ed ligand motifs. An alignment of Ed and Ek protein sequences to the recently reported HLA-DR1 pocket residues is in agreement with observed anchor residues in Ek and Ed motifs, thus confirming the predicted similarity of mouse class II E molecules with human DR molecules. Furthermore, this alignment was extended to the putative pockets of class II Eb and E* molecules, and allowed, together with sequence information of previously Identified natural ligands of Eb and E5 molecules, a prediction of their respective motifs. The information obtained by this study should be useful to identify putative class II E epltopes in proteins and to design peptides for blocking class II E molecule

Characterization of the ribonuclease activity on the skin surface

The rapid degradation of ribonucleic acids (RNA) by ubiquitous ribonucleases limits the efficacy of new therapies based on RNA molecules. Therefore, our aim was to characterize the natural ribonuclease activities on the skin and in blood plasma i.e. at sites where many drugs in development are applied. On the skin surfaces of Homo sapiens and Mus musculus we observed dominant pyrimidine-specific ribonuclease activity. This activity is not prevented by a cap structure at the 5'-end of messenger RNA (mRNA) and is not primarily of a 5'- or 3'-exonuclease type. Moreover, the ribonuclease activity on the skin or in blood plasma is not inhibited by chemical modifications introduced at the 2'OH group of cytidine or uridine residues. It is, however, inhibited by the ribonuclease inhibitor RNasin(® )although not by the ribonuclease inhibitor SUPERase· In™. The application of our findings in the field of medical science may result in an improved efficiency of RNA-based therapies that are currently in development

iSPOT: A Web Tool for the Analysis and Recognition of Protein Domain Specificity

Methods that aim at predicting interaction partners are very likely to play an important role in the interpretation of genomic information. iSPOT (iSpecificity Prediction Of Target) is a web tool (accessible at http://cbm.bio.uniroma2.it/iSPOT) developed for the prediction of protein-protein interaction mediated by families of peptide recognition modules. iSPOT accesses a database of position specific residue-residue interaction frequencies for members of the SH3 and PDZ protein domain families. The software utilises this database to provide a score for any potential domain peptide interaction