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Biology subjects

Church, G.

Publications and source records attributed to Church, G..

46 records · Page 3Linked to original sources

In vivo multi-dimensional information-keeping in Halobacterium salinarum

Shortage of raw materials needed to manufacture components for silicon-based digital memory storage has led to a search for alternatives, including systems for storing texts, images, movies and other forms of information in DNA. Use of DNA as a medium for storage of 3-D information has also been investigated. However, two problems have yet to be addressed: first, storage of 3-D information in DNA has used objects and coding schemes which require large volumes of data; second, the medium used for DNA information-keeping has been inconsistent with qualities needed for long-term data storage. Here, we address these problems. First, we created in vivo DNA-encoded digital archives holding precise specifications for 3- and 4-dimensional figures with unprecedented efficiency. Second, we have demonstrated more robust and longer-lasting information-carriers than earlier repositories for DNA-based data archives by inserting digital information into the halophile, Halobacterium salinarum, an extremophilic archaeon. We then embedded Information-keeping halophiles into crystalline mineral salts in which similar organisms have been shown to persist in stasis for hundreds of millions of years. We propose that digital information archives composed in 3 or more dimensions may be inserted into halophilic organisms and preserved intact for indefinite periods of time.

synthetic biology↗

Deep Learning for RNA Synthetic Biology

Engineered RNA elements are programmable tools capable of detecting small molecules, proteins, and nucleic acids. Predicting the behavior of these tools remains a challenge, a situation that could be addressed through enhanced pattern recognition from deep learning. Thus, we investigate Deep Neural Networks (DNN) to predict toehold switch function as a canonical riboswitch model in synthetic biology. To facilitate DNN training, we synthesized and characterized in vivo a dataset of 91,534 toehold switches spanning 23 viral genomes and 906 human transcription factors. DNNs trained on nucleotide sequences outperformed (R2=0.43-0.70) previous state-of-the-art thermodynamic and kinetic models (R2=0.04-0.15) and allowed for human-understandable attention-visualizations (VIS4Map) to identify success and failure modes. This deep learning approach constitutes a major step forward in engineering and understanding of RNA synthetic biology. One Sentence SummaryDeep neural networks are used to improve functionality prediction and provide insights on toehold switches as a model for RNA synthetic biology tools.

bioengineering↗

A robust benchmark for germline structural variant detection

New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution, and comprehensiveness. Translating these methods to routine research and clinical practice requires robust benchmark sets. We developed the first benchmark set for identification of both false negative and false positive germline SVs, which complements recent efforts emphasizing increasingly comprehensive characterization of SVs. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle (GIAB) Consortium integrated 19 sequence-resolved variant calling methods, both alignment- and de novo assembly-based, from short-, linked-, and long-read sequencing, as well as optical and electronic mapping. The final benchmark set contains 12745 isolated, sequence-resolved insertion and deletion calls [≥]50 base pairs (bp) discovered by at least 2 technologies or 5 callsets, genotyped as heterozygous or homozygous variants by long reads. The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.66 Gbp and 9641 SVs supported by at least one diploid assembly. Support for SVs was assessed using svviz with short-, linked-, and long-read sequence data. In general, there was strong support from multiple technologies for the benchmark SVs, with 90 % of the Tier 1 SVs having support in reads from more than one technology. The Mendelian genotype error rate was 0.3 %, and genotype concordance with manual curation was >98.7 %. We demonstrate the utility of the benchmark set by showing it reliably identifies both false negatives and false positives in high-quality SV callsets from short-, linked-, and long-read sequencing and optical mapping.

genomics↗

A haplotype-aware de novo assembly of related individuals using pedigree graph

MotivationReconstructing high-quality haplotype-resolved assemblies for related individuals of various species has important applications in understanding Mendelian diseases along with evolutionary and comparative genomics. Through major genomics sequencing efforts such as the Personal Genome Project, the Vertebrate Genome Project (VGP), the Earth Biogenome Project (EBP) and the Genome in a Bottle project (GIAB), a variety of sequencing datasets from mother-father-child trios of various diploid species are becoming available.\n\nCurrent trio assembly approaches are not designed to incorporate long-read sequencing data from parents in a trio, and therefore require relatively high coverages of costly long-read data to produce high-quality assemblies. Thus, building a trio-aware assembler capable of producing accurate and chromosomal-scale diploid genomes in a pedigree, while being cost-effective in terms of sequencing costs, is a pressing need of the genomics community.\n\nResultsWe present a novel pedigree-graph-based approach to diploid assembly using accurate Illumina data and long-read Pacific Biosciences (PacBio) data from all related individuals, thereby generalizing our previous work on single individuals. We demonstrate the effectiveness of our pedigree approach on a simulated trio of pseudo-diploid yeast genomes with different heterozygosity rates, and real data from Arabidopsis Thaliana. We show that we require as little as 30x coverage Illumina data and 15x PacBio data from each individual in a trio to generate chromosomal-scale phased assemblies. Additionally, we show that we can detect and phase variants from generated phased assemblies.\n\nAvailabilityhttps://github.com/shilpagarg/WHdenovo\n\nContactshilpa_garg@hms.harvard.edu, gchurch@genetics.med.harvard.edu

bioinformatics↗

Rapid and scalable in vitro production of single-stranded DNA

We present a rapid, scalable, user-friendly method for in vitro production of high-purity single-stranded DNA (ssDNA) ranging from 89-3315 nucleotides in length. PCR with a forward primer bearing a methanol-responsive polymer generates a tagged amplicon that enables selective precipitation of the modified strand under denaturing conditions. We demonstrate that the recovered ssDNA can be used for CRISPR/Cas9 homology-directed repair in human cells, DNA-origami folding, and fluorescent in situ hybridization.

molecular biology↗

Rational design of a compact CRISPR-Cas9 activator for AAV- mediated delivery

Akin to Zinc Finger and Transcription Activator Like Effector based transcriptional modulators, nuclease-null CRISPR-Cas9 provides a groundbreaking programmable DNA binding platform, begetting an arsenal of targetable regulators for transcriptional and epigenetic perturbation, by either directly tethering, or recruiting, transcription enhancing effectors to either component of the Cas9/guide RNA complex. Application of these programmable regulators is now gaining traction for the modulation of disease-causing genes or activation of therapeutic genes, in vivo. Adeno-Associated Virus (AAV) is an optimal delivery vehicle for in vivo delivery of such regulators to adult somatic tissue, due to the efficacy of viral delivery with minimal concerns about immunogenicity or integration. However, present Cas9 activator systems are notably beyond the packaging capacity of a single AAV delivery vector capsid. Here, we engineer a compact CRISPR-Cas9 activator for convenient AAV-mediated delivery. We validate efficacy of the CRISPR-Cas9 transcriptional activation using AAV delivery in several cell lines.

synthetic biology↗

Accurate analysis of genuine CRISPR editing events with ampliCan

We present ampliCan, an analysis tool for genome editing that unites highly precise quantification and visualization of genuine genome editing events. ampliCan features nuclease-optimized alignments, filtering of experimental artifacts, event-specific normalization, off-target read detection and quantifies insertions, deletions, HDR repair as well as targeted base editing. It is scalable to thousands of amplicon sequencing-based experiments from any genome editing experiment, including CRISPR. It enables automated integration of controls and accounts for biases at every step of the analysis. We benchmarked ampliCan on both real and simulated datasets against other leading tools, demonstrating that it outperformed all in the face of common confounding factors.

bioinformatics↗

High-throughput creation and functional profiling of eukaryotic DNA sequence variant libraries using CRISPR/Cas9

Construction of genetic variant libraries with phenotypic measurement is central to advancing todays functional genomics, and remains a grand challenge. Here, we introduce a Cas9-based approach for generating pools of mutants with defined genetic alterations (deletions, substitutions and insertions), along with methods for tracking their fitness en masse. We demonstrate the utility of our approach in performing focused analysis of hundreds of mutants of a single protein and in investigating the biological function of an entire family of poorly characterized genetic elements. Our platform allows fundamental biology questions to be investigated in a quick, easy and affordable manner.

bioengineering↗

Inter-homologue repair in fertilized human eggs?

Many human diseases have an underlying genetic component. The development and application of methods to prevent the inheritance of damaging mutations through the human germline could have significant health benefits, and currently include preimplantation genetic diagnosis and carrier screening. Ma et al. take this a step further by attempting to remove a disease mutation from the human germline through gene editing1. They assert the following advances: (i) the correction of a pathogenic gene mutation responsible for hypertrophic cardiomyopathy in human embryos using CRISPR-Cas9 and (ii) the avoidance of mosaicism in edited embryos. In the case of correction, the authors conclude that repair using the homologous chromosome was as or more frequent than mutagenic nonhomologous end-joining (NHEJ). Their conclusion is significant, if validated, because such a \"self-repair\" mechanism would allow gene correction without the introduction of a repair template. While the authors analyses relied on the failure to detect mutant alleles, here we suggest approaches to provide direct evidence for inter-homologue recombination and discuss other events consistent with the data. We also review the biological constraints on inter-homologue recombination in the early embryo.

cell biology↗

Systemic post-translational control of bacterial metabolism regulates adaptation in dynamic environments

Across all domains of life, elaborate control mechanisms regulate proteins, pathways, and cell phenotypes as organisms adapt to ever-changing environments. Post-translational modifications (PTMs) allow cells to rapidly and reversibly regulate molecular pathways, but it remains unclear how individual PTMs regulate fitness. Here, we studied >130 PTM sites in Escherichia coli to unravel how PTMs regulate cell metabolism and fitness in response to environmental changes, such as the glucose-acetate diauxie. Using a new metabolic modeling approach, we found a significant fraction of post-translationally modified enzymes are predicted to control shifts in pathway usage following evolutionarily-important environmental changes. Genetic screens using Multiplex Automated Genome Engineering confirmed that these PTMs impact cellular fitness, especially under dynamically changing environments. Finally, mechanisms of how individual PTMs impact protein function were detailed using molecular dynamics simulations and enzyme assays for enolase, transaldolase, and serine hydroxymethyltransferase. Thus, by integrating whole-cell data and pathway modeling with detailed biochemical analysis, we unraveled how individual PTMs regulate enzymes, pathways, and phenotypes to adapt to sudden environmental changes.

systems biology↗