This work reports the development and spectroscopic studies of blinking-suppressed compact quantum dots. It is shown that a linearly graded alloy shell can be grown on a small CdSe core via a precisely controlled layer-by-layer process, and that this graded shell leads to a dramatic suppression of QD blinking both in organic solvents and in water. A substantial portion (over 25%) of the resulting QDs essentially does not blink (more than 99% of the time in the bright or “on” state). Theoretical modeling studies indicate that this type of linearly graded and relatively thin shells can not only minimize charge carrier access to surface traps, but also reduce accumulated lattice strains and defects at the core/shell interface, both of which are believed to be responsible for carrier trapping and QD blinking. Further, the biological utility of blinking-suppressed QDs by using both polyethylene glycol (PEG)-based and multidentate capping ligands is evaluated, and the results show that their optical properties are maintained regardless of surface coatings or solvating media, and that the blinking-suppressed QDs can provide continuous trajectories in live cell receptor tracking studies.

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<p dir="ltr">Single molecule localization microscopy (SMLM) has become an essential tool in imaging nanoscale biological structures. It breaks the diffraction limit by utilizing photo-switchable or photo-convertible fluorophores to obtain isolated single molecule emission patterns (i.e. PSFs) and subsequently localize the molecule’s position with a precision down to ~ 20 to 80 nm laterally-axially. However, optical aberrations compromise its spatial resolution. Additionally, conventional SMLM algorithms require sparse activation to reduce emission pattern overlap, which restricts imaging speed and temporal resolution, thus limiting its utility in dynamic live cell imaging. In this study, we first conducted a comprehensive quantitative analysis of the theoretical precision limits for position and wavefront distortion measurements in the presence of aberrations, which enhances our understanding of aberration effects in SMLM and lays the groundwork for developing more effective aberration correction methods. To improve temporal resolution, we developed a high-density single molecule localization algorithm that utilizes deep learning to analyze molecule blinking data. This approach allows us to achieve high localization precision and resolve structures at tens of nanometers resolution, even with highly overlapped blinking data. Validated by both simulated and high-density experimental data, our algorithm successfully resolves the complex structures of various cellular organelles and captures rapid dynamic movements in live cells. This work addresses the knowledge gap about aberrations in SMLM and expands its applications to more dynamic and detailed studies of cellular processes.</p>

In the circular Escherichia coli chromosome, two replisomes are assembled at the unique origin of replication and drive DNA synthesis in opposite directions until they meet in the terminus region across from the origin. Despite the difference in rates of the two replisomes, their arrival at the terminus is synchronized through a highly specialized system consisting of the terminator protein (Tus) bound to the termination sites (Ter). This synchronicity is mediated by the polarity of the Tus−Ter complex that stops replisomes from one direction (non-permissive face) but not the other (permissive face). Two oppositely oriented clusters of five Tus–Ters that each block one of the two replisomes create a “replication fork trap” for the first arriving replisome while waiting for the late arriving one. Despite extensive biochemical and structural studies, the molecular mechanism behind Tus−Ter polar arrest activity remained controversial. Moreover, none of the previous work provided answers for the long-standing discrepancy between the ability of Tus−Ter to permanently stop replisomes in vitro and its low efficiency in vivo. Here, I spearheaded a collaborative project that combined single-molecule DNA replication assays, X-ray crystallography and binding studies to provide a true molecular-level understanding of the underlying mechanism of Tus−Ter polar arrest activity. We showed that efficiency of Tus−Ter is determined by a head-to-head kinetic competition between rate of strand separation by the replisome and rate of rearrangement of Tus−Ter interactions during the melting of the first 6 base pairs of Ter. This rearrangement maintains Tus’s strong grip on the DNA and stops the advancing replisome from breaking into Tus−Ter central interactions, but only transiently. We further showed how this kinetic competition functions within the context of two mechanisms to impose permanent fork stoppage. The rate-dependent fork arrest activity of Tus−Ter explains its low efficiency in vivo and why contradictory in vitro results from previous studies have led to controversial elucidations of the mechanism. It also provides the first example where the intrinsic heterogeneity in rate of individual replisomes could have different biological outcomes in its communication with double-stranded DNA-binding protein barriers.

<p>  </p> <p>        Analyzing single molecule emission patterns plays a critical role in retrieving the structural and physiological information of their tagged targets, and further, understanding their interactions and cellular context. These emission patterns of tiny light sources (i.e. point spread functions, PSFs) simultaneously encode information such as the molecule’s location, orientation, the environment within the specimen, and the paths the emitted photons took before being captured by the camera. However, retrieving multiple classes of information beyond the 3D position from complex or high-dimensional single molecule data remains challenging, due to the difficulties in perceiving and summarizing a comprehensive yet succinct model. We developed smNet, a deep neural network that can extract multiplexed information near the theoretical limit from both complex and high-dimensional point spread functions. Through simulated and experimental data, we demonstrated that smNet can be trained to efficiently extract both molecular and specimen information, such as molecule location, dipole orientation, and wavefront distortions from complex and subtle features of the PSFs, which otherwise are considered too complex for established algorithms. </p> <p>        Single molecule localization microscopy (SMLM) forms super-resolution images with a resolution of several to tens of nanometers, relying on accurate localization of molecules’ 3D positions from isolated single molecule emission patterns. However, the inhomogeneous refractive indices distort and blur single molecule emission patterns, reduce the information content carried by each detected photon, increase localization uncertainty, and thus cause significant resolution loss, which is irreversible by post-processing. To compensate tissue induced aberrations, conventional sensorless adaptive optics methods rely on iterative mirror-changes and image-quality metrics to compensate aberrations. But these metrics result in inconsistent, and sometimes opposite, metric responses which fundamentally limited the efficacy of these approaches for aberration correction in tissues. Bypassing the previous iterative trial-then-evaluate processes, we developed deep learning driven adaptive optics (DL-AO), for single molecule localization microscopy (SMLM) to directly infer wavefront distortion and compensate distortion near real-time during data acquisition. our trained deep neural network monitors the individual emission patterns from single molecule experiments, infers their shared wavefront distortion, feeds the estimates through a dynamic filter (Kalman), and drives a deformable mirror to compensate sample induced aberrations. We demonstrated that DL-AO restores single molecule emission patterns approaching the conditions untouched by specimen and improves the resolution and fidelity of 3D SMLM through brain tissues over 130 µm, with as few as 3-20 mirror changes.</p>

Gene regulation mediated by transcription factors (TFs) is essential for all organisms. The functionality of TFs can largely be described by the fraction of time they occupy their regulatory binding sites on the chromosome. DNA-binding proteins have been shown to find their targets through facilitated diffusion in vitro. In its simplest form this means that the protein combines a random 3D search in the cytoplasm with 1D sliding along DNA. This has been proposed to speed up target location. It is difficult to mimic the in vivo conditions for gene regulation in biochemistry experiments; i.e. the ionic strength, chromosomal structure, and the presence of other DNA-binding macromolecules.    In this thesis single molecule imaging assays for live cell measurements were developed to study the kinetics of the Escherichia coli transcription factor LacI. The low copy number LacI, in fusion with a fluorescent protein (Venus) is detected as a localized near-diffraction limited spot when being DNA-bound for longer than the exposure time. An allosteric inducer is used to control binding and release. Using this method we can measure the time it takes for LacI to bind to different operator sequences. We then extend the assay and show that LacI slides in to and out from the operator site, and that it is obstructed by another DNA-binding protein positioned next to its target. We present a new model where LacI redundantly passes over the operator many times before binding.    By combining experiments with molecular dynamics simulations we can characterize the details of non-specific DNA-binding. In particular, we validate long-standing assumptions that the non-specific association is diffusion-controlled. In addition it is seen that the non-specifically bound protein diffuses along DNA in a helical path.    Using microfluidics we design a chase assay to measure in vivo dissociation rates for the LacI-Venus dimer. Based on the comparison of these rates with association rates and equilibrium binding data we suggest that there might be a short time following TF dissociation when transcription initiation is silenced. This implies that the fraction of time the operator is occupied is not enough to describe the regulatory range of the promoter.

In recent years, semiconductor quantum dots (QDs) have arisen as a new class of fluorescent probes that possess unique optical and electronic properties well-suited for single-molecule imaging of dynamic live cell processes. Nonetheless, the large size of conventional QD-ligand constructs has precluded their widespread use in single-molecule studies, especially on cell interiors. A typical QD-ligand construct can range upwards of 35 nm in diameter, well exceeding the size threshold for cytosolic diffusion and posing steric hindrance to binding cell receptors. The objective of this research is to develop tagging strategies that allow QD-ligand conjugates to specifically bind their target proteins while maintaining a small overall construct size. To achieve this objective, we utilize the HaloTag protein (HTP) available from Promega Corporation, which reacts readily with a HaloTag ligand (HTL) to form a covalent bond. When HaloTag ligands are conjugated to size-minimized multidentate polymer coated QDs, compact QD-ligand constructs less than 15 nm in diameter can be produced. These quantum dot-HaloTag ligand (QD-HTL) conjugates can then be used to covalently bind and track cellular receptors genetically fused to the HaloTag protein. In this study, size-minimized quantum dot-HaloTag ligand conjugates are synthesized and evaluated for their ability to bind specifically to purified and cellular HTP. The effect of QD-HTL surface modifications on different types of specific and nonspecific cellular binding are systematically investigated. Finally, these QD-HTL conjugates are utilized for single-molecule imaging of dynamic live cell processes. Our results show that size-minimized QD-HTLs exhibit great promise as novel imaging probes for live cell imaging, allowing researchers to visualize cellular protein dynamics in remarkable detail.

La protéine SRSF1, aussi appelée ASF/SF2, fait partie de la famille des protéines SR, une famille de protéines liant l’ARN très conservées. Ces protéines jouent un rôle régulateur de l’épissage, également lors de l’épissage alternatif. Une centaine d’ARN cible ont été décrits pour SRSF1 mais la manière dont SRSF1 sélectionne ses cibles parmi tous les pré-ARNm est mal comprise. Des études in vitro et in vivo ont montré que les protéines SR reconnaissent un petit motif dégénéré qui est souvent présent en plusieurs copies dans les ESE («enhancer splicing element »). Bien que les protéines SR lient ces motifs avec une faible spécificité, la définition des exons se fait avec une grande fidélité. Afin de mieux comprendre le mécanisme d’action de SRSF1, j’ai réalisé une étude cinétique des interactions SRSF1-ARN dans les cellules vivantes par des techniques de microscopies avancées. Grâce au système CRISPR, j’ai pu étiqueter la protéine SRSF1 avec la protéine Halo puis j’ai combiné une technique de photo-blanchiment (FRAP) et une technique de suivi de particule unique (« single particle tracking, SPT) pour mesurer la diffusion de SRSF1 et son affinité pour l’ARN. J’ai mesuré la durée de vie des événements de liaison individuellement aussi bien sur le pool global de pré-ARNm que sur des cibles spécifiques. Nos résultats indiquent que la liaison de SRSF1 ne dépasse pas quelques secondes, même sur les cibles de haute affinité. Cette cinétique rapide permet à SRSF1 d’être en contact avec l’ensemble des transcrits naissants qui est produit en permanence dans la cellule. De plus, mon travail apporte une analyse cinétique de la dynamique des snRNP à la résolution de la molécule unique dans le nucléoplasme des cellules vivantes. Nous avons déterminé les coefficients de diffusion des snRNP et la durée de leur association à l’ARN dans ces cellules. / SRSF1, formerly known as ASF/SF2, belongs to the SR protein family, which is a conserved family of RNA-binding protein that plays essential roles as regulators of both constitutive and alternative splicing. Hundreds of RNA targets have been described for SRSF1 but how SRSF1 selects its targets from the entire pool of cellular pre-mRNAs remains an open question. In vitro and in vivo studies have shown that SR proteins recognize short degenerated motifs often present in multiple copies at ESEs. Similar cryptic motifs are however frequently present in pre-mRNAs, and this low specificity of binding contrasts with the great fidelity of exon definition. To better understand the mechanism of action of SRSF1, I performed a kinetic study of SRSF1-RNA interactions in live cells using advanced microscopic techniques. Taking advantage by the CRISPR system, I tagged endogenous SRSF1 with Halo protein, and I combined photobleaching (FRAP) and single particle tracking (SPT) techniques to estimate diffusion and binding rates of SRSF1. I measured the duration of individual binding events, both on the cellular pool of pre-mRNAs and on specific targets. Our results indicate that binding of SRSF1 does not exceed few seconds, even on high-affinity targets. This rapid kinetics allows SRSF1 to rapidly sample the entire pool of nascent RNAs continuously produced in cells. Moreover, we provided a kinetic analysis of snRNP dynamics at a single-molecule resolution in the nucleoplasm of living cells. Our results enabled us to determine diffusion coefficients of snRNPs and their RNA binding duration in vivo.

Authors are permitted to post the MBoC PDF of their articles (and/or supplemental material) on their personal websites or in an online institutional repository provided there appears always the proper citation of the manuscript in MBoC and a link to the original publication of the manuscript in MBoC (http://www.molbiolcell.org/site/misc/ifora.xhtml) / 京都大学 / 0048 / 新制・課程博士 / 博士(生命科学) / 甲第19869号 / 生博第350号 / 新制||生||46(附属図書館) / 32905 / 京都大学大学院生命科学研究科統合生命科学専攻 / (主査)教授 河内 孝之, 教授 藤田 尚志, 教授 永尾 雅哉 / 学位規則第4条第1項該当 / Doctor of Philosophy in Life Sciences / Kyoto University / DFAM

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