Molecular computing devices, compared to conventional computers, have the clear advantage of small size (enabling insertion into living cells), as well as the ability to interact directly with their biological surroundings due to their inherent biological nature, thus holding the promise for biomedical applications. The long-term vision of the project is to create nano-sized biological computers equipped with medical knowledge that will roam our bodies, search for and diagnose diseases, and autonomously treat them by administering a therapeutic biomolecule. These smart drugs (drugs active only under specific conditions) will enable greater specificity in comparison to traditional drugs.
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This project aims at developing methods that enables editing DNA molecules with word processing ease, based on novel computation, biochemical, and robotic methods. In this project, a computer algorithm designs an optimal protocol for the synthesis of a specific long fragment of DNA or DNA libraries, and generates a robot program to implement this optimized protocol in a fully automated manner in a short period of time. The ability to edit many DNA fragments according to specification, such as new genes, holds promise to significantly enhance the progress of this biomedical research.
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THIS IS THE ONLY PROJECT ACTIVE IN OUR LAB
Our lab pioneered the concept, the mathematical foundations, as well as the implementation of utilizing somatic mutations naturally acquired by individual cells, to reconstruct cell lineage trees among cells of multi-cellular organisms and applied it to various questions of biological and medical importance.
- Quantifying the ability to reconstruct a cell-lineage tree using somatic mutations. The development of cells within a multi-cellular organism has similarities to the development of populations, and hence is amenable to study using concepts and tools of population genetics. In particular, the reconstruction of a cell lineage tree, capturing the cell division history of organism cells, can be attempted by applying algorithms and techniques of population genetics to somatic mutations accumulated during cell division. Yet, cell populations possess unique features that are absent or rare in organism populations (e.g. the presence of stem cells and a small number of generations since the zygote). Our group developed a method for reconstructing cell lineage trees using highly unstable microsatellite loci. We used extensive measurements of somatic mutations in individual single cells isolated from different healthy and diseased tissues from mice and humans. The validation was done by analyzing the ability to infer known and clear biological scenarios. In general we found that if the biological scenario is simple, almost all algorithms checked can infer it. Another somewhat surprising conclusion is that the best algorithm from those we checked uses absolute distance as the distance measure and Neighbour Joining as the clustering tool.
- Lineage analysis of intestinal epithelial cells. We have developed a method for single cell extraction of epithelial cells from single intestinal crypts using a modification of the crypt isolation technique. Our findings confirmed that colon crypts are monoclonal and that, throughout adulthood, the process of monoclonal conversion plays a major role in the maintenance of crypts. The absence of immortal strand mechanism in crypts stem cells was validated by the age-dependent accumulation of microsatellite mutations. In addition, we confirmed the positive correlation between physical and lineage proximity of crypts, by showing that the colon is separated into small domains that share a common ancestor. We gained new data demonstrating that colon epithelium is clustered separately from hematopoietic and other cell types, indicating that the colon is constituted of few progenitors and ruling out significant renewal of colonic epithelium from hematopoietic cells during adulthood. Overall, our study demonstrates the reliability of cell lineage reconstruction for the study of stem cell dynamics, and it further addresses open questions in colon stem cells. In addition, this method can be applied to study stem cell dynamics in other systems.
- Lineage analysis of muscle-bound primordial stem cells from myofiber-associated myogenic and nonmyogenic progenitors. We applied a method for reconstructing cell lineage trees from somatic mutations to MSCs and myogenic and non-myogenic cells from individual myofiber that were cultured at clonal density. Our analyses show that (i) in addition to myogenic progenitors, myofibers also harbor non-myogenic progenitors of a distinct, yet close, lineage; (ii) myofiber-associated non-myogenic and myogenic cells share the same muscle-bound primordial stem cells of a lineage distinct from bone marrow MSCs. (iii) these muscle-bound primordial stem-cells first part to individual muscles and then differentiate into myogenic and non-myogenic stem cells.
- Lineage analysis of mouse oocytes. We analyze acquired somatic mutations to reconstruct lineage trees of hundreds of oocytes and other cells, sampled from mismatch-repair deficient mice at various ages. We discovered that in the reconstructed lineage trees oocytes cluster distinctly from cells of bone marrow origin, show no lineage barrier between ovaries and increase in depth (number of cell divisions since the zygote) with mouse age, an increase accelerated after unilateral ovariectomy. The deeper oocytes observed in older mice may be prenatal, entailing depth-guided oocyte maturation, or post-natal, entailing oocyte renewal in the adult mouse. Our results argue against massive exposure to stimulating hormone that is routinely practiced to treat infertility.
- Lineage analysis of human leukemia cells. Human cancers display substantial intra-tumoral genetic heterogeneity, which facilitates tumor survival under changing micro environmental conditions. Tumor substructure and its impact on disease progression and relapse are incompletely understood. In the current study, a high-throughput method that utilizes neutral somatic mutations accumulated in individual cells to reconstruct cell lineage trees was applied to hundreds of cells of human acute leukemia harvested from multiple patients at diagnosis and at relapse. The reconstructed cell lineage trees of acute myeloid leukemia (AML) patients demonstrated that leukemia cells at relapse were shallow (divide rarely) compared to cells at diagnosis and were closely related to their stem cell subpopulation, implying that in these instances relapse might have originated from rarely dividing stem cells. In contrast, among acute lymphoid leukemia (ALL) patients, no differences in cell depth were observed between diagnosis and relapse. In one case of chronic myeloid leukemia (CML), at blast crisis, most of the cells at relapse were mismatch-repair deficient. In almost all leukemia cases, more than one lineage was observed at relapse, indicating that diverse mechanisms can promote relapse in the same patient. In conclusion, diverse relapse mechanisms can be observed by systematic reconstruction of cell lineage trees of leukemia patients.
- Next Generation Sequencing (NGS). The unabated progress in DNA sequencing technologies is fostering a wave of genomics, epigenomics, transcriptomics and proteomics technologies. These sequencing-based technologies are increasingly being targeted to individual cells, which will allow many new and longstanding questions to be addressed. In our studies we use Mismatch-Repair (MMR)-deficient mice and focus on Microsatellites (MS), short tandem repeats, (STRs), which are repeated sequences of 1-6 base-pairs of DNA. Shapiro‘s lab pioneered the concept, the mathematical foundations, as well as the implementation of utilizing somatic mutations naturally acquired by individual cells to reconstruct cell lineage trees. The first high-throughput implementation of the approach utilized the capillary electrophoresis method for measuring somatic mutations in MS and provided new insights into a broad spectrum of questions ranging from the origin of cancer metastasis to crypt dynamics and the origin of muscle stem cells. The current state-of-the-art employs advanced lab automation for amplification of every sampled cell over a panel of about 128 MS, and identifies somatic MS mutations (additions or subtractions of MS repeats) in each cell through computational analysis of capillary electrophoresis fragment analysis, which is sufficient to obtain sufficient resolution in MMR-deficient mice (in which MS are relatively unstable). To enable better resolution and reduce per-cell costs, we adapted our process to use readouts of high-throughput sequencing, and subsequently expand the MS panel by at least 5 orders of magnitude. In addition this technology will be automated hoping to eventually reach a panel of 50,000 microsatellites per cell, which will be barcoded and sequenced cost-effectively using extensive multiplexing. Retrieving this unprecedented amount of microsatellite sequencing data from each individual cell and increasing throughput via automation would enable precise cell lineage tree reconstruction and allow us to explore questions on lineage depth and topology in mice and in human samples that are currently not accessible to any available method.