Comparison of seven single cell whole genome amplification commercial kits using targeted sequencing.

Advances in whole genome amplification (WGA) techniques enable understanding of the genomic sequence at a single cell level. Demand for single cell dedicated WGA kits (scWGA) has led to the development of several commercial kit. To this point, no robust comparison of all available kits was performed.

Comparing algorithms that reconstruct cell lineage trees utilizing information on microsatellite mutations.

Organism cells proliferate and die to build, maintain, renew and repair it. The cellular history of an organism up to any point in time can be captured by a cell lineage tree in which vertices represent all organism cells, past and present, and directed edges represent progeny relations among them. The root represents the fertilized egg, and the leaves represent extant and dead cells.

A library of programmable DNAzymes that operate in a cellular environment.

DNAzymes were used as inhibitory agents in a variety of experimental disease settings, such as cancer, viral infections and even HIV. Drugs that become active only upon the presence of preprogrammed abnormal environmental conditions may enable selective molecular therapy by targeting abnormal cells without injuring normal cells. Here we show a novel programmable DNAzyme library composed of variety of Boolean logic gates, including YES, AND, NOT, OR, NAND, ANDNOT, XOR, NOR and 3-input-AND gate, that uses both miRNAs and mRNAs as inputs.

Cell lineage analysis of acute leukemia relapse uncovers the role of replication-rate heterogeneity and microsatellite instability.

Human cancers display substantial intratumoral genetic heterogeneity, which facilitates tumor survival under changing microenvironmental conditions. Tumor substructure and its effect on disease progression and relapse are incompletely understood. In the present study, a high-throughput method that uses 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.

Cell lineage analysis of the mammalian female germline.

Fundamental aspects of embryonic and post-natal development, including maintenance of the mammalian female germline, are largely unknown. Here we employ a retrospective, phylogenetic-based method for reconstructing cell lineage trees utilizing somatic mutations accumulated in microsatellites, to study female germline dynamics in mice. Reconstructed cell lineage trees can be used to estimate lineage relationships between different cell types, as well as cell depth (number of cell divisions since the zygote).

Muscle-bound primordial stem cells give rise to myofiber-associated myogenic and non-myogenic progenitors.

Myofiber cultures give rise to myogenic as well as to non-myogenic cells. Whether these myofiber-associated non-myogenic cells develop from resident stem cells that possess mesenchymal plasticity or from other stem cells such as mesenchymal stem cells (MSCs) remain unsolved. To address this question, we applied a method for reconstructing cell lineage trees from somatic mutations to MSCs and myogenic and non-myogenic cells from individual myofibers that were cultured at clonal density.

Colon stem cell and crypt dynamics exposed by cell lineage reconstruction.

Stem cell dynamics in vivo are often being studied by lineage tracing methods. Our laboratory has previously developed a retrospective method for reconstructing cell lineage trees from somatic mutations accumulated in microsatellites. This method was applied here to explore different aspects of stem cell dynamics in the mouse colon without the use of stem cell markers.

Detection of multiple disease indicators by an autonomous biomolecular computer.

The promise of biomolecular computers is their ability to interact with naturally occurring biomolecules, enabling in the future the development of context-dependent programmable drugs. Here we show a context-sensing mechanism of a biomolecular automaton that can simultaneously sense different types of molecules, allowing future integration of biomedical knowledge on a broad range of molecular disease symptoms in the decision of a biomolecular computer to release a drug molecule.

Recursive construction and error correction of DNA molecules and libraries from synthetic and natural DNA.

Making error-free, custom DNA assemblies from potentially faulty building blocks is a fundamental challenge in synthetic biology. Here, we show how recursion can be used to address this challenge using a recursive procedure that constructs error-free DNA molecules and their libraries from error-prone synthetic oligonucleotides and naturally existing DNA. Specifically, we describe how divide and conquer (D&C), the quintessential recursive problem-solving technique, is applied in silico to divide target DNA sequences into overlapping, albeit error prone, oligonucleotides, and how recursive construction is applied in vitro to combine them to form error-prone DNA molecules.

Recursive construction of perfect DNA molecules from imperfect oligonucleotides.

Making faultless complex objects from potentially faulty building blocks is a fundamental challenge in computer engineering, nanotechnology and synthetic biology. Here, we show for the first time how recursion can be used to address this challenge and demonstrate a recursive procedure that constructs error-free DNA molecules and their libraries from error-prone oligonucleotides. Divide and Conquer (D&C), the quintessential recursive problem-solving technique, is applied in silico to divide the target DNA sequence into overlapping oligonucleotides short enough to be synthesized directly, albeit with errors; error-prone oligonucleotides are recursively combined in vitro, forming error-prone DNA molecules; error-free fragments of these molecules are then identified, extracted and used as new, typically longer and more accurate, inputs to another iteration of the recursive construction procedure; the entire process repeats until an error-free target molecule is formed.

Estimating cell depth from somatic mutations.

The depth of a cell of a multicellular organism is the number of cell divisions it underwent since the zygote, and knowing this basic cell property would help address fundamental problems in several areas of biology. At present, the depths of the vast majority of human and mouse cell types are unknown. Here, we show a method for estimating the depth of a cell by analyzing somatic mutations in its microsatellites, and provide to our knowledge for the first time reliable depth estimates for several cells types in mice.

Reconstruction of cell lineage trees in mice.

The cell lineage tree of a multicellular organism represents its history of cell divisions from the very first cell, the zygote. A new method for high-resolution reconstruction of parts of such cell lineage trees was recently developed based on phylogenetic analysis of somatic mutations accumulated during normal development of an organism. In this study we apply this method in mice to reconstruct the lineage trees of distinct cell types.

Stochastic computing with biomolecular automata.

Stochastic computing has a broad range of applications, yet electronic computers realize its basic step, stochastic choice between alternative computation paths, in a cumbersome way. Biomolecular computers use a different computational paradigm and hence afford novel designs. We constructed a stochastic molecular automaton in which stochastic choice is realized by means of competition between alternative biochemical pathways, and choice probabilities are programmed by the relative molar concentrations of the software molecules coding for the alternatives.

An autonomous molecular computer for logical control of gene expression.

Early biomolecular computer research focused on laboratory-scale, human-operated computers for complex computational problems. Recently, simple molecular-scale autonomous programmable computers were demonstrated allowing both input and output information to be in molecular form. Such computers, using biological molecules as input data and biologically active molecules as outputs, could produce a system for 'logical' control of biological processes.

Human combinatorial Fab library yielding specific and functional antibodies against the human fibroblast growth factor receptor 3.

The human combinatorial antibody library Fab 1 (HuCAL-Fab 1) was generated by transferring the heavy and light chain variable regions from the previously constructed single-chain Fv library (Knappik, A., Ge, L., Honegger, A.

DNA molecule provides a computing machine with both data and fuel.

The unique properties of DNA make it a fundamental building block in the fields of supramolecular chemistry, nanotechnology, nano-circuits, molecular switches, molecular devices, and molecular computing. In our recently introduced autonomous molecular automaton, DNA molecules serve as input, output, and software, and the hardware consists of DNA restriction and ligation enzymes using ATP as fuel. In addition to information, DNA stores energy, available on hybridization of complementary strands or hydrolysis of its phosphodiester backbone.

Differential activation of cysteine-substitution mutants of fibroblast growth factor receptor 3 is determined by cysteine localization.

Various human skeletal disorders are thought to be caused by mutations in fibroblast growth factor receptor 3 (FGFR3). These result in chronic FGFR3 hyperactivation and inhibition of bone growth. One such disorder, thanatophoric dysplasia, the most common form of sporadic, lethal dwarfism, is associated frequently with cysteine substitutions (G370C, S371C, and Y373C) in the extracellular juxtamembrane region of the receptor.