Visualizing single cells and their organization in intact tissue is crucial to understanding their governing biological function. Even though single cell RNA sequencing has provided many insights into the heterogeneity and gene expression profiles across many tissue types, the dissociation process which loses the spatial information is hindering our deeper understanding of how these transcriptional distinct cell types are organized and interacting in their native tissue environment.
\r\n\r\nThe thesis begins by giving a background on how single cell RNA sequencing has transformed biology and the emergence of spatial technology such as sequential fluorescence in situ hybridization (seqFISH). While spatial methods are useful for mapping the cell types identified from single cell RNA sequencing, the need for turning spatial technology such as seqFISH, which has high detection efficiency of the transcriptome with spatial information, into an in situ discovery tool is discussed as the scientific community\u2019s goal heads towards building spatial atlases for every human tissues and organs such as the brain.
\r\n \r\nWhile seqFISH has high detection efficiency, it is still limited in the number of genes capable of profiling at once. The major obstacle is the optical crowding problems when more RNA species are targeted and imaged using a fluorescence microscope. In Chapter 2, we first investigated, if the RNA molecules are instead captured on a coverslip and profiled with sequential barcoding strategy, the FISH-based method will reliably characterize the transcriptome when molecular crowding is not an issue.
\r\n \r\nFinally, in Chapter 3, we demonstrate the barcoding strategy to break through the molecular crowding limit of multiplexed FISH. From being able to profile hundreds to a thousand genes by various multiplexed FISH methods at that time in the field, we succeeded in profiling 10,000 genes by RNA seqFISH+, an evolved version of seqFISH, in various intact tissue sections, turning seqFISH+ into a spatial discovery technology with its genome-wide coverage and high detection efficiency. The work described in this part of the thesis is highlighted in Nature Method\u2019s Method of The Year 2020- Spatially-resolved Transcriptomic article.
", "doi": "10.7907/nvfe-5j74", "publication_date": "2021", "thesis_type": "phd", "thesis_year": "2021" }, { "id": "thesis:14227", "collection": "thesis", "collection_id": "14227", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:06022021-012404326", "primary_object_url": { "basename": "Thesis-YodaiTakei-final.pdf", "content": "final", "filesize": 50506093, "license": "other", "mime_type": "application/pdf", "url": "/14227/1/Thesis-YodaiTakei-final.pdf", "version": "v4.0.0" }, "type": "thesis", "title": "Integrated Spatial Genomics Reveals Organizational Principles of Single-Cell Nuclear Architecture", "author": [ { "family_name": "Takei", "given_name": "Yodai", "orcid": "0000-0002-7226-5185", "clpid": "Takei-Yodai" } ], "thesis_advisor": [ { "family_name": "Cai", "given_name": "Long", "orcid": "0000-0002-7154-5361", "clpid": "Cai-Long" } ], "thesis_committee": [ { "family_name": "Elowitz", "given_name": "Michael B.", "orcid": "0000-0002-1221-0967", "clpid": "Elowitz-M-B" }, { "family_name": "Guttman", "given_name": "Mitchell", "orcid": "0000-0003-4748-9352", "clpid": "Guttman-M" }, { "family_name": "Rothenberg", "given_name": "Ellen V.", "orcid": "0000-0002-3901-347X", "clpid": "Rothenberg-E-V" }, { "family_name": "Cai", "given_name": "Long", "orcid": "0000-0002-7154-5361", "clpid": "Cai-Long" } ], "local_group": [ { "literal": "div_bbe" } ], "abstract": "Three-dimensional (3D) nuclear architecture plays key roles in many cellular processes such as gene regulation and genome replication. Recent sequencing-based and imaging-based single-cell studies have characterized a high variability of nuclear features in individual cells from a wide-range of measurement modalities, such as chromosome structures, subnuclear structures, chromatin states, and nascent transcription. However, the lack of technologies that allow us to interrelate those nuclear features simultaneously in the same single cells limits our understanding of nuclear architecture. To overcome this limitation, a technology that can examine 3D nuclear features across modalities from the same single cells is required. Here, we demonstrate integrated spatial genomics approaches, which enable genome-wide investigation of chromosome structures, subnuclear structures, chromatin states, and transcriptional states in individual cells. In Chapter 2, we introduce the \"track first and identify later\" approach, which enables multiplexed tracking of genomic loci in live cells by combining CRISPR/Cas9 live imaging and DNA sequential fluorescence in situ hybridization (DNA seqFISH) technologies. We demonstrate our approach by resolving the dynamics of 12 unique subtelomeric loci in mouse embryonic stem (ES) cells. In Chapter 3, we present the intron seqFISH technology, which enables transcriptome-scale gene expression profiling at their nascent transcription active sites in individual nuclei in mouse ES cells and fibroblasts, along with mRNA and lncRNA seqFISH and immunofluorescence. We show the transcription active sites position at the surfaces of chromosome territories with variable inter-chromosomal organization in individual nuclei. By building upon those technologies, in Chapter 4, we demonstrate integrated spatial genomics in mouse ES cells, which enables to image thousands of genomic loci by DNA seqFISH+, along with sequential immunofluorescence and RNA seqFISH in individual cells. We show \"fixed loci\" that are invariably associated with specific subnuclear structures across hundreds of single cells that can constrain nuclear architecture in individual nuclei. In addition, we find individual genomic loci appear to be pre-positioned to specific nuclear compartments with different frequencies, which are independent from nascent transcriptional states of single cells. Lastly, in Chapter 5, we demonstrate the integrated spatial genomics technology in the mouse brain cortex, enabling the investigation of single-cell nuclear architecture in a cell-type specific fashion as well as the exploration of common organizational principles of nuclear architecture across cell types. We reveal that inter-chromosomal organization and radial positioning of chromosomes are arranged with cell-type specific chromatin fixed loci and subnuclear structure organization in diverse cell types. We also uncover the variable organization of chromosome domain structures at the sub-megabase scale in individual cells, which can be obscured with bulk measurements. Together, these results demonstrate the ability of integrated spatial genomics to advance our overall understanding of single-cell nuclear architecture in various biological systems.
", "doi": "10.7907/4ces-zm75", "publication_date": "2021", "thesis_type": "phd", "thesis_year": "2021" }, { "id": "thesis:11718", "collection": "thesis", "collection_id": "11718", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:06072019-153337463", "primary_object_url": { "basename": "Thesis-Yandong Zhang-Final.pdf", "content": "final", "filesize": 2182617, "license": "other", "mime_type": "application/pdf", "url": "/11718/1/Thesis-Yandong Zhang-Final.pdf", "version": "v5.0.0" }, "type": "thesis", "title": "Highly Multiplexed Imaging of E. Coli Chromosome and Sensitive Detection of Single-Cell Protein", "author": [ { "family_name": "Zhang", "given_name": "Yandong", "orcid": "0000-0003-3291-9209", "clpid": "Zhang-Yandong" } ], "thesis_advisor": [ { "family_name": "Cai", "given_name": "Long", "clpid": "Cai-Long" } ], "thesis_committee": [ { "family_name": "Beauchamp", "given_name": "Jesse L.", "clpid": "Beauchamp-J-L" }, { "family_name": "Ismagilov", "given_name": "Rustem F.", "clpid": "Ismagilov-R-F" }, { "family_name": "Rees", "given_name": "Douglas C.", "clpid": "Rees-D-C" }, { "family_name": "Cai", "given_name": "Long", "clpid": "Cai-Long" } ], "local_group": [ { "literal": "div_chem" } ], "abstract": "The driving force for biology research is the development of new techniques which allow high-sensitivity, high-throughput measurement in various contexts. Over the past decade, the emerging of a variety of single-cell techniques have greatly transformed our understanding of biological system. My thesis work was therefore focused on development of new single- cell techniques and use the techniques to generate new insights into biological system. Specifically, in the first part of my thesis work, we developed DNA seqFISH, a technique that allows us to image more than 100 different loci on the chromosome in single cells. We applied this technique to image E. coli chromosome with 50kb genomic resolution and 50nm spatial precision. Our data allows us to parse the E. coli chromosome structure according to their different spatial conformations and different cell-cycle stages. We identified two chromosome conformations with distinct domain structures, which is obscured from previous population-average research. We further characterized the domain structure dynamics during daughter chromosome segregation. Therefore, our data provides a high- resolution, dynamic view of E. coli chromosome structure.
\r\n\r\nIn the second part, we developed a novel method for sensitive detection of targeted protein and its post-translational modification (PTM) isoform in single cells. Instead of depending on antibodies to distinguish targeted protein and its PTM isoform, we developed an efficient covalent barcoding strategy to barcode targeted protein inside the cells. Thereafter, targeted protein and its PTM isoform are separated by conventional gel electrophoresis, while their single-cell identity is preserved in the covalently attached oligo. By counting the attached DNA oligos using next-generation sequencing, targeted protein, and its PTM isoform can be accurately measured. We demonstrated the utility of the technology by quantification of histone protein, H2B and its mono-ubiquitination isoform, H2Bub at single-cell level. Our method revealed the single-cell heterogeneities of H2Bub/H2B ratio and its cell-cycle dynamics. Our method therefore provides an antibody-free method for sensitive detection of proteins and its isoforms in single cells.
", "doi": "10.7907/CDSX-MR28", "publication_date": "2019", "thesis_type": "phd", "thesis_year": "2019" }, { "id": "thesis:10966", "collection": "thesis", "collection_id": "10966", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:05292018-192944407", "type": "thesis", "title": "Noncommutative Biology: Sequential Regulation of Complex Networks and Connected Matter", "author": [ { "family_name": "Letsou", "given_name": "William Peter", "orcid": "0000-0002-4969-2330", "clpid": "Letsou-William-Peter" } ], "thesis_advisor": [ { "family_name": "Cai", "given_name": "Long", "clpid": "Cai-Long" } ], "thesis_committee": [ { "family_name": "Weitekamp", "given_name": "Daniel P.", "clpid": "Weitekamp-D-P" }, { "family_name": "Campbell", "given_name": "Judith L.", "clpid": "Campbell-J-L" }, { "family_name": "Murray", "given_name": "Richard M.", "clpid": "Murray-R-M" }, { "family_name": "Cai", "given_name": "Long", "clpid": "Cai-Long" } ], "local_group": [ { "literal": "div_chem" } ], "abstract": "During animal development from zygote to adult, a limited set of regulatory molecules are autonomously deployed in the service of tissue-specific gene expression (reviewed in chapter 1). Inherent in the process is the tension that single cells sample heterogeneous expression states while robustly maintaining a collective final outcome. This thesis addresses theoretical issues that help resolve the paradox that one cell simultaneously contains the fate information of many.
\r\n\r\nPrevious models of development have likened cell fate to minima on a smooth potential energy surface. Such static pictures can be misleading because they suggest the egg knows the path it will take to the adult before it divides even once. Recognition that the potential analogy is an oversimplification has led others to propose that the surface is actually nonsmooth. Chapter 2 reviews the theoretical basis for smooth potentials and resolves these problems by appealing to the tangent space of gene expression. It is then shown that if the potential difference is sufficient to characterize the difference between egg and adult, then the tangent space controls on gene expression are one-dimensional. Furthermore, a shortcoming of models ignoring the connectivity and common origin of dividing cells is that they erect artificial barriers between alternative fates. A fundamentally different picture is sketched wherein the difference between egg and adult is schematized as the shape of the locus of equipotential fates accessible at the same point in time. The conjugacy of space and time is invoked to explain how the requirement that each fate be on a line of equipotential is the same as requiring that each alternative fate move the same distance down the surface at each step. The developmental trajectory is deterministic but not known in advance because it needs to be ascertained at each step which way cells \"turn\" in order to maintain their equipotential relationship. Chapters 3 and 4 refine this sequential model of collective development with specific examples.
\r\n\r\nA simple solution to the problem of cell-type specific gene expression is combinatorial binding of transcription factors at promoters. It is shown in chapter 3 that such models result in substantial information bottlenecks, because all cell fate information is concentrated at the start. We explore a novel, noncommutative model of gene regulation—known as sequential logic—that spreads the information out over time. It is shown using time sequences of noncommutative controllers that targets which otherwise would have been activated together can be regulated independently. We derive scaling laws for two noncommutative models of regulation, motivated by phosphorylation/neural networks and chromosome folding, respectively, and show that they scale super-exponentially in the number of regulators. It is also shown that specificity in control is robust to loss of a regulator. Consequently, sequential logic overcomes the information bottleneck in complex problems and enables novel solutions through roundabout strategies. The theoretical results are connected to real biological networks demonstrating specificity in the context of promiscuity.
\r\n\r\nNoncommutative sequential logic has improved storage capacity, but it does not specify who or what supplies the sequences of input that determine cell fate. Chapter 4 offers a solution by way of the seemingly unrelated problem of looping in twisted strings. Cells and strings obey a set of common space-time constraints, ultimately due to the conservation of energy. It is argued that the most parsimonious allocation of energy from the straight to strained string is the one in which each segment sees the same share of the total. Planar looping is shown to be a consequence of the parsimony principle and the Euler-Poincaré equations for rotational motion in the presence an applied torque. We then solve the problem for the looping of a twisted string; with two strains, the Euler-Poincaré predict a different answer than the classical Frenet-Serret equations. Using the results of chapter 2, it is concluded that the Frenet-Serret curvatures assigned ahead of time are not guaranteed to generate space curves that conserve energy: the predicted string has localized strains the Euler-Poincaré solution lacks. Rotational dynamics of strings are connected to developing organisms by postulating conserved RNA polymerase as an analog of angular momentum, and transcriptional activity as energy. Alternative fates along a one-dimensional \"string\" of dividing cells are possible by finding the RNAP distribution that conserves transcriptional activity along a curve of constant developmental potential. Consequently, each alternative fate samples a different sequence of changes to the distribution as it follows a local gradient downhill from high to low developmental potential over time.
\r\n\r\nIn conclusion, regulation in the tangent space of gene expression resolves the paradox that development has a unique solution specified in the DNA of the egg which cannot be determined with certainty until completion of the adult. Noncommutative sequential logic generates complexity that cannot be realized at the start, while interdependent cells (and strings) require time to ensure that each fate is at the same potential difference from a common ancestor. This fundamental reimagining of the Waddington framework can be tested using new multiplexed mRNA imaging technologies that preserve the spatial context of cells in developing tissue.
", "doi": "10.7907/9B5E-F105", "publication_date": "2018", "thesis_type": "phd", "thesis_year": "2018" }, { "id": "thesis:9995", "collection": "thesis", "collection_id": "9995", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:12152016-144548062", "type": "thesis", "title": "Highly Multiplexed Single Cell In Situ RNA Detection", "author": [ { "family_name": "Shah", "given_name": "Sheel Mukesh", "orcid": "0000-0002-6321-4669", "clpid": "Shah-Sheel-Mukesh" } ], "thesis_advisor": [ { "family_name": "Cai", "given_name": "Long", "clpid": "Cai-Long" } ], "thesis_committee": [ { "family_name": "Gradinaru", "given_name": "Viviana", "clpid": "Gradinaru-V" }, { "family_name": "Elowitz", "given_name": "Michael B.", "clpid": "Elowitz-M-B" }, { "family_name": "Allman", "given_name": "John Morgan", "clpid": "Allman-J-M" }, { "family_name": "Cai", "given_name": "Long", "clpid": "Cai-Long" } ], "local_group": [ { "literal": "div_bbe" } ], "abstract": "Identifying the genetic basis of cellular function and identity has become a central question in understanding the functioning of complex biological systems in recent years. Single cell sequencing techniques have provided a great deal of insight into the transcriptional profiles of various cell types. However, single cell RNAseq studies require cells to be removed from their native environments resulting in the loss of spatial relationships between cells and suffer from low detection efficiency. Moving forward, a central question in further understanding large biological systems consisting of many disparate cell types will be how do these cells interact with each other to form functional tissues. To accomplish this goal, a method that keeps the tissue architecture intact is required. Single molecule fluorescence in situ hybridization (smFISH) is one such technique, but suffers from a lack of multiplex measurement capability as only a very few genes can be measured in any given sample and has low signal to noise ratio. Here I present a method that overcomes the low signal to noise ratio by using an amplification technique known as single molecule hybridization chain reaction (smHCR). smHCR coupled with the existing sequential FISH (seqFISH) method, which overcomes the inherent multiplexing limit of smFISH, provides a powerful tool to measure the copy numbers of 100\u2019s of genes in single cell in situ.
\r\n\r\nThe mouse brain contains 100,000,000 cells arranged into distinct anatomical structures. While cell types have been previously characterized by morphology and electrophysiology, single cell RNA sequencing has recently identified many cell types based on gene expression profiles. On the other hand, the Allen Brain Atlas (ABA) provides a systematic gene expression database using in situ hybridization (ISH) of the entire mouse brain, but lacks the ability to correlate the expression of different genes in the same cell. Using the smHCR-seqFISH technique to measure the expression profiles of up to 249 genes in single cells in coronal brain sections, we have identified distinct cell clusters based on the expression profiles of 15000 cells and observed spatial patterning of cells in the hippocampus. In the dentate gyrus, we resolved lamina-layered patterns of cell clusters with a clear separation between the granule cell layer and the sub-granular zone. In CA1 and CA3, the data revealed distinct subregions, each with unique combinations of cell clusters. Particularly, we observed that the dorso-lateral CA1 is almost completely cellular homogeneous with increasing cellular heterogeneity on the dorsal to ventral axis. Together, these results demonstrate the power of highly multiplex in situ analysis to the brain, with further application to a wide range of biological systems.
", "doi": "10.7907/Z9X63JXH", "publication_date": "2017", "thesis_type": "phd", "thesis_year": "2017" }, { "id": "thesis:9589", "collection": "thesis", "collection_id": "9589", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:02262016-115004310", "primary_object_url": { "basename": "elubeck_thesis_sub2.pdf", "content": "final", "filesize": 27206724, "license": "other", "mime_type": "application/pdf", "url": "/9589/1/elubeck_thesis_sub2.pdf", "version": "v4.0.0" }, "type": "thesis", "title": "Towards in situ Single Cell Systems Biology", "author": [ { "family_name": "Lubeck", "given_name": "Eric", "orcid": "0000-0002-5457-0258", "clpid": "Lubeck-Eric" } ], "thesis_advisor": [ { "family_name": "Cai", "given_name": "Long", "clpid": "Cai-Long" } ], "thesis_committee": [ { "family_name": "Sternberg", "given_name": "Paul W.", "clpid": "Sternberg-P-W" }, { "family_name": "Elowitz", "given_name": "Michael B.", "clpid": "Elowitz-M-B" }, { "family_name": "Gradinaru", "given_name": "Viviana", "clpid": "Gradinaru-V" }, { "family_name": "Cai", "given_name": "Long", "clpid": "Cai-Long" } ], "local_group": [ { "literal": "div_chem" } ], "abstract": "Systems-level studies of biological systems rely on observations taken at a resolution lower than\r\nthe essential unit of biology, the cell. Recent technical advances in DNA sequencing have enabled\r\nmeasurements of the transcriptomes in single cells excised from their environment, but it remains a\r\ndaunting technical problem to reconstruct in situ gene expression patterns from sequencing data. In\r\nthis thesis I develop methods for the routine, quantitative in situ measurement of gene expression\r\nusing fluorescence microscopy.
\r\n\r\nThe number of molecular species that can be measured simultaneously by fluorescence microscopy\r\nis limited by the pallet of spectrally distinct fluorophores. Thus, fluorescence microscopy is traditionally\r\nlimited to the simultaneous measurement of only five labeled biomolecules at a time. The\r\ntwo methods described in this thesis, super-resolution barcoding and temporal barcoding, represent\r\nstrategies for overcoming this limitation to monitor expression of many genes in a single cell.\r\nSuper-resolution barcoding employs optical super-resolution microscopy (SRM) and combinatorial\r\nlabeling via-smFISH (single molecule fluorescence in situ hybridization) to uniquely label individual\r\nmRNA species with distinct barcodes resolvable at nanometer resolution. This method dramatically\r\nincreases the optical space in a cell, allowing a large numbers of barcodes to be visualized\r\nsimultaneously. As a proof of principle this technology was used to study the S. cerevisiae calcium\r\nstress response. The second method, sequential barcoding, reads out a temporal barcode through\r\nmultiple rounds of oligonucleotide hybridization to the same mRNA. The multiplexing capacity of\r\nsequential barcoding increases exponentially with the number of rounds of hybridization, allowing\r\nover a hundred genes to be profiled in only a few rounds of hybridization.
\r\n\r\nThe utility of sequential barcoding was further demonstrated by adapting this method to study\r\ngene expression in mammalian tissues. Mammalian tissues suffer both from a large amount of\r\nauto-fluorescence and light scattering, making detection of smFISH probes on mRNA difficult. An\r\namplified single molecule detection technology, smHCR (single molecule hairpin chain reaction),\r\nwas developed to allow for the quantification of mRNA in tissue. This technology is demonstrated\r\nin combination with light sheet microscopy and background reducing tissue clearing technology,\r\nenabling whole-organ sequential barcoding to monitor in situ gene expression directly in intact\r\nmammalian tissue.
\r\n\r\nThe methods presented in this thesis, specifically sequential barcoding and smHCR, enable multiplexed\r\ntranscriptional observations in any tissue of interest. These technologies will serve as a\r\ngeneral platform for future transcriptomic studies of complex tissues.
", "doi": "10.7907/Z9BK1999", "publication_date": "2016", "thesis_type": "phd", "thesis_year": "2016" } ]