Biology subjects

Wang, B.

Publications and source records attributed to Wang, B..

At least 667 records · Page 37Linked to original sources

bioRxiv2019

The role of swnR gene on the biosynthesis pathway of the swainsonine in Metarhizium anisopliae

Swainsonine (SW) is the principal toxic ingredient of locoweeds, and is produced by fungi including Metarhizium anisopliae, Slafractonia leguminicola, and Alternaria oxytropis. Studies of the SW biosynthesis pathway in these fungi have demonstrated the requirement for a swnK gene and the presence of a variety of other SWN cluster genes, but have not determined a precise role for the swnR gene, which encodes a NADB Rossmann-fold reductase, nor if it is necessary for the biosynthesis of SW. In this study, we used homologous recombination (HR) to knock out the swnR gene of M. anisopliae to determine its effect on the SW biosynthesis pathway. The concentration of SW was measured in the fermentation broth of M. anisopliae at 1 d, 3 d, 5 d and 7 d using a Q Exactive Mass Spectrometer. The gene for swnR was detected by RT-qPCR. To determine the role of the swnR gene in the SW biosynthesis pathway of M. anisopliae, we used PEG-mediated homologous recombination (HR) to transform a wild-type strain (WT) with a Benomyl (ben)-resistant fragment to knock out the swnR gene producing a mutant-type strain (MT). A complemented-type (CT) strain was produced by adding a complementation vector that contains the glufosinate (herbicide) resistance (bar) gene as a marker. The content of SW decreased, but was not eliminated in the fermentation broth of the MT strain, and returned to the original level in the CT strain. These results indicate that the swnR gene plays a crucial role in the SW biosynthesis pathway of M. anisopliae, but suggests that another gene in the fungus may share the function of swnR.

molecular biology↗

bioRxiv2019

Semiparametric Partial Common Principal Component Analysis for Covariance Matrices

SO_SCPLOWUMMARYC_SCPLOWWe consider the problem of jointly modeling multiple covariance matrices by partial common principal component analysis (PCPCA), which assumes a proportion of eigenvectors to be shared across covariance matrices and the rest to be individual-specific. This paper proposes consistent estimators of the shared eigenvectors in PCPCA as the number of matrices or the number of samples to estimate each matrix goes to infinity. We prove such asymptotic results without making any assumptions on the ranks of eigenvalues that are associated with the shared eigenvectors. When the number of samples goes to infinity, our results do not require the data to be Gaussian distributed. Furthermore, this paper introduces a sequential testing procedure to identify the number of shared eigenvectors in PCPCA. In simulation studies, our method shows higher accuracy in estimating the shared eigenvectors than competing methods. Applied to a motor-task functional magnetic resonance imaging data set, our estimator identifies meaningful brain networks that are consistent with current scientific understandings of motor networks during a motor paradigm.

neuroscience↗

bioRxiv2019

Upstream translation initiation expands the coding capacity of segmented negative-strand RNA viruses

Segmented negative-strand RNA viruses (sNSVs) include the influenza viruses, the bunyaviruses, and other major pathogens of humans, other animals and plants. The genomes of these viruses are extremely short. In response to this severe genetic constraint, sNSVs use a variety of strategies to maximise their coding potential. Because the eukaryotic hosts parasitized by sNSVs can regulate gene expression through low levels of translation initiation upstream of their canonical open reading frames (ORFs), we asked whether sNSVs could use upstream translation initiation to expand their own genetic repertoires. Consistent with this hypothesis, we showed that influenza A viruses (IAVs) and bunyaviruses were capable of upstream translation initiation. Using a combination of reporter assays and viral infections, we found that upstream translation in IAVs can initiate in two unusual ways: through non-AUG initiation in virally encoded untranslated regions, and through the appropriation of an AUG-containing leader sequence from host mRNAs through viral cap-snatching, a process we termed start-snatching. Finally, while upstream translation of cellular genes is mainly regulatory, for sNSVs it also has the potential to create novel viral gene products. If in frame with a viral ORF, this creates N-extensions of canonical viral proteins. If not, it allows the expression of cryptic overlapping ORFs, which we found were highly conserved in IAV and widely distributed in peribunyaviruses. Thus, by exploiting their hosts capacity for upstream translation initiation, sNSVs can expand still further the coding potential of their extremely compact RNA genomes.

molecular biology↗

bioRxiv2019

Broadly Conserved Roles of TMEM-131 Family Proteins in Intracellular Collagen Assembly and Secretory Cargo Trafficking

Collagen is the most abundant protein in animals. Its dysregulation contributes to ageing and human disorders including tissue fibrosis in major organs. How premature collagens in the endoplasmic reticulum (ER) assemble and route for secretion remains molecularly undefined. From an RNAi screen, we identified an uncharacterized C. elegans gene tmem-131, deficiency of which impairs collagen production and activates ER stress response. TMEM-131 N-termini contain bacterial PapD chaperone-like (PapD-L) domains essential for collagen assembly and secretion. Human TMEM131 binds to COL1A2 and TRAPPC8 via N-terminal PapD-L and C-terminal domain, respectively, to drive collagen production. We provide evidence that previously undescribed roles of TMEM131 in collagen recruitment and secretion are evolutionarily conserved in C. elegans, Drosophila and humans.

cell biology↗

bioRxiv2019

Field decomposition of Bt-506 corn leaf and its effect on Collembola in the black soil region of China

The litters of Bt corn would go into the soil through straw returning and field ploughing after cultivation. To clarify whether the leaf litter decomposition rate and the non-target soil Collembola were influenced by the Bt protein or other litter properties in leaf litters of Bt corn in Northeast China, leaf litterbags of Bt-506, its near isoline Zheng 58 and a local type Zhengdan 958 were used in the field in Northeast China. The leaf decomposition rate, the leaf properties and the collembolan community in litterbags were investigated later. After seven months, only 43.5 ng/g Bt protein in Bt-506 leaf litter was left. All the investigated indices were not significantly different between Bt-506 and its near isoline Zheng 58. But when compared with local type Zhengdan 958, Bt-506 and its near isoline Zheng 58 contained lower non-structural carbohydrate content but higher total nitrogen content, and had lower litter decomposition rate and less abundance of Collembola. Collembolan abundance and litter decomposition rate were both significantly correlated with the non-structural carbohydrate and total nitrogen contents of the leaf litters. Field study results revealed Bt protein did not affect the leaf litter decomposition rate and the collembolan community in leaf litterbags in short term. The significant differences of these investigated indices among corn types were caused by the different non-structural carbohydrate and total nitrogen contents in leaf litter.

ecology↗

bioRxiv2019

Enhancing Myocardial Repair with CardioClusters

BackgroundCellular therapy to treat heart failure is an ongoing focus of intense research and development, but progress has been frustratingly slow due to limitations of current approaches. Engineered augmentation of established cellular effectors overcomes impediments, enhancing reparative activity with improved outcomes relative to conventional techniques. Such next generation implementation includes delivery of combinatorial cell populations exerting synergistic effects. Concurrent isolation and expansion of three distinct cardiac-derived interstitial cell types from human heart tissue, as previously reported by our group, prompted design of a three-dimensional (3D) structure that maximizes cellular interaction, allows for defined cell ratios, controls size, enables injectability, and minimizes cell losses upon delivery. MethodsThree distinct populations of human cardiac interstitial cells including mesenchymal stem cells (MSCs), endothelial progenitor cells (EPCs), and c-Kit+ cardiac interstitial cells (cCICs) when cultured together spontaneously form scaffold-free 3D microenvironments termed CardioClusters. Biological consequences of CardioCluster formation were assessed by multiple assays including single cells RNA-Seq transcriptional profiling. Protective effects of CardioClusters in vitro were measured using cell culture models for oxidative stress and myocardial ischemia in combination with freshly isolated neonatal rat ventricular myocytes. Long-term impact of adoptively transferred CardioClusters upon myocardial structure and function in a xenogenic model of acute infarction using NODscid mice was assessed over a longitudinal time course of 20-weeks. ResultsCardioCluster design enables control over composite cell types, cell ratios, size, and preservation of structural integrity during delivery. Profound changes for biological properties of CardioClusters relative to constituent parental cell populations include enhanced expression of stem cell-relevant factors, adhesion/extracellular-matrix molecules, and cytokines. The CardioCluster 3D microenvironment maximizes cellular interaction while maintaining a more native transcriptome similar to endogenous cardiac cells. CardioCluster delivery improves cell retention following intramyocardial injection with preservation of long-term cardiac function relative to monolayer-cultured cells when tested in an experimental murine infarction model followed for up to 20 weeks post-challenge. CardioCluster-treated hearts show increases in capillary density, preservation of cardiomyocyte size, and reduced scar size indicative of blunting pathologic infarction injury. ConclusionsCardioClusters are a novel next generation development and delivery approach for cellular therapeutics that potentiate beneficial activity and enhance protective effects of human cardiac interstitial cell mixed populations. CardioClusters utilization in this preclinical setting establishes fundamental methodologic and biologic insights, laying the framework for optimization of CardioCluster design to provide greater efficacy in cell-based therapeutic interventions intended to mitigate cardiomyopathic damage.

cell biology↗

bioRxiv2019

The periphery and the core properties explain the omnigenic model in the human interactome

Understanding the connectivity patterns of genes in a localized disease neighborhood or disease module in a molecular interaction network (interactome) is a key step toward advancing the knowledge about molecular mechanisms underlying a complex disease. In this work, we introduce a framework that detects peripheral and core regions of a disease in the human interactome. We leverage gene expression data on 104 diseases and analyze the connectivity of differentially expressed genes (quantified by a p-value < 0.05) and their topological membership in the network to distinguish between peripheral and core genes. Per definition, peripheral and core genes are topologically different and we show that they also differ biologically. Core genes are more enriched for Genome-wide association study (GWAS) and Online Mendelian Inheritance in Man (OMIM) data, whereas peripheral genes are more shared across different disease states and their overlap helps predict disease proximity in the human interactome. Based on this observation, we propose a flower model to explain the organization of genes in the human interactome, with core genes of different diseases as the petals and the peripheral genes as the (shared) stem. We show that this network model is an important step towards finding novel drug targets and improving disease classification. Overall, we were able to demonstrate how perturbations percolate through the human interactome and contribute to peripheral and core regions, an important novel feature of the omnigenic model.

systems biology↗

bioRxiv2019

Generating Templates and Growth Charts for School-Aged Brain Development

Standard brain templates and growth charts provide an invaluable resource for basic science research, with the eventual goal of contributing to the clinical care of neuropsychiatric conditions. Here, we report on a protocol to generate MRI brain templates in children and adolescents at one-year intervals from 6-to-18 years of age, with their corresponding growth charts, using a large-scale neuroimaging data resource (948 brain images from China and United States). To assure that the brain templates and growth charts are reliable and accurate, we developed a refined pipeline consisting of template construction, image registration, brain area labeling and growth chart modeling. The pipeline comprises multiple modular workflows that can be used for multiple applications. In our approach, population- and age-specific templates were first constructed to avoid systemic bias in registration. Brain areas were then labeled based on the appropriate templates, and their morphological metrics were extracted for modeling associated growth curves. We implemented warp cost as a function of age differences between individual brains and template brains. A strong U-shaped cost function was revealed, indicating larger age differences are associated with greater registration errors. This validates the necessity of age-specific reference templates in pediatric brain imaging studies. Growth chart analyses revealed preferential shape differences between Chinese and US samples in lateral frontal and parietal areas, aspects of cortex which are most variable across individuals with regard to structure and function as well as associated behavioral performance. This growth distinction is largely driven by neurodevelopmental differences between Chinese and US age-specific brain templates. The pipeline together with the brain templates and charts are publicly available and integrated into the Connectome Computation System.

neuroscience↗

bioRxiv2019

BRD2 regulation of sigma-2 receptor expression upon cytosolic cholesterol deprivation

Traditionally a pharmacologic target for antipsychotic treatment, the sigma-2 receptor (S2R) was recently implicated in cholesterol homeostasis. Here we investigated the transcriptional regulation of S2R by the Bromo/ExtraTerminal epigenetic reader family (BETs, including BRD2, 3, 4) upon cholesterol perturbation.\n\nCytosolic cholesterol deprivation was induced using an export blocker of lysosomal cholesterol in ARPE19 cells. This condition upregulated mRNA and protein levels of S2R, and of SREBP2 but not SREBP1, transcription factors key to cholesterol/fatty acid metabolism. Silencing BRD2 but not BRD4 (though widely deemed as a master regulator) or BRD3 prevented S2R upregulation induced by cholesterol deprivation. Silencing SREBP2 but not SREBP1 diminished S2R expression. Furthermore, BRD2 co-immunoprecipitated with the SREBP2 transcription-active N-terminal domain, and chromatin immunoprecipitation-qPCR showed a BRD2 occupancy at the S2R gene promoter.\n\nIn summary, this study reveals a novel BRD2/SREBP2 cooperative regulation of S2R transcription in response to cytosolic cholesterol deprivation, thus shedding new light on epigenetic control of cholesterol biology.

biochemistry↗

bioRxiv2019

Silencing epigenetic writer DOT1L attenuates intimal hyperplasia

ObjectiveHistone methyltransferases are emerging targets for epigenetic therapy. DOT1L (disruptor of telomeric silencing 1-like) is the H3K79 methylation writer. We investigated its role in the development of intimal hyperplasia (IH).\n\nApproach and ResultsIH was induced via balloon angioplasty in rat carotid arteries. DOT1L and its catalytic products H3K79me2 and H3K79me3 (immunostaining) increased by 4.69 {+/-}0.34, 2.38 {+/-}0.052, and 3.07 {+/-}0.27 fold, respectively, in injured (versus uninjured) carotid arteries at post-injury day 7. DOT1L silencing via shRNA-lentivirus infusion in injured arteries reduced DOT1L, H3K79me2, and IH at day 14 by 54.5%, 37.1%, and 76.5%, respectively. Moreover, perivascular administration of a DOT1L-selective inhibitor (EPZ5676) reduced H3K79me2, H3K79me3, and IH by 56.1%, 58.6%, and 39.9%, respectively.\n\nConclusionsDOT1L inhibition mitigates the development of IH.

pathology↗

bioRxiv2019

E-cadherin binds glycosylated sodium-taurocholate cotransporting polypeptide to facilitate hepatitis B virus entry

Hepatitis B virus (HBV) continues to pose a serious public health risk and is one of the major causes of chronic liver disease and hepatocellular carcinoma. Current antiviral therapy does not effectively eradicate HBV and, thus, further investigation into the mechanisms employed by HBV to allow for invasion of host cells, is critical for the development of novel therapeutic agents. Sodium-taurocholate cotransporting polypeptide (NTCP) has been identified as a functional receptor for HBV. However, the specific mechanism by which HBV and NTCP interact remains unclear. Herein we show that the expression of E-cadherin was upregulated in cells expressing HBV, while knockdown of E-cadherin in HepG2-NTCP cells, HepaRG cells and primary human hepatocytes served to significantly inhibit infection by HBV and HBV pseudotyped particles. Alternatively, exogenous E-cadherin expression was found to significantly enhance HBV uptake by HepaRG cells. Further, mechanistic studies identified glycosylated NTCP localized to the cell membrane via E-cadherin binding, which subsequently allowed for more efficient binding between NTCP and the preS1 of the large HBV surface proteins. E-cadherin was also found to play a key role in establishing and maintaining hepatocyte polarity, which is essential for efficient HBV infection. These observations suggest that E-cadherin facilitates HBV entry through regulation of NTCP distribution and hepatocyte polarity.\n\nAuthor SummaryHepatitis B Virus (HBV) still seriously endangers public health. It is very important to understand the mechanism of HBV invading host cells for developing new therapy target. Sodium-taurocholate cotransporting polypeptide (NTCP) is the key receptor mediating HBV invasion, while other molecules also exhibit important roles in ensuring efficient and productive HBV infection. This study reports that E-cadherin facilitates HBV entry by directly interacting with glycosylated NTCP to mediate its distribution on the hepatocyte membrane and also affects the efficacy of HBV invasion by influncing hepatocyte polarity.

microbiology↗

bioRxiv2019

Adding Extra Knowledge in Scalable Learning of Sparse Differential Gaussian Graphical Models

We focus on integrating different types of extra knowledge (other than the observed samples) for estimating the sparse structure change between two p-dimensional Gaussian Graphical Models (i.e. differential GGMs). Previous differential GGM estimators either fail to include additional knowledge or cannot scale up to a high-dimensional (large p) situation. This paper proposes a novel method KDiffNet that incorporates Additional Knowledge in identifying Differential Networks via an Elementary Estimator. We design a novel hybrid norm as a superposition of two structured norms guided by the extra edge information and the additional node group knowledge. KDiffNet is solved through a fast parallel proximal algorithm, enabling it to work in large-scale settings. KDiffNet can incorporate various combinations of existing knowledge without re-designing the optimization. Through rigorous statistical analysis we show that, while considering more evidence, KDiffNet achieves the same convergence rate as the state-of-the-art. Empirically on multiple synthetic datasets and one real-world fMRI brain data, KDiffNet significantly outperforms the cutting edge baselines with regard to the prediction performance, while achieving the same level of time cost or less.

bioinformatics↗

bioRxiv2019

Precise annotation of human, chimpanzee, rhesus macaque and mouse mitochondrial genomes using 5’ and 3’ end small RNAs

Using 5 and 3 end small RNAs, we annotated human, chimpanzee, rhesus macaque and mouse mitochondrial genomes at 1 base-pair (bp) resolution to cover both strands of the mammalian mitochondrial genome entirely without leaving any gaps or overlaps. The precise annotation of all coding and non-coding genes (e.g. ncMT1, MDL2 and MDL1AS) led to the discovery of novel functions and mechanisms of mitochondrion. In this study, we defined the conserved sequence block (CSB) region to span five CSBs (CSB1, CSB2, CSB3, LSP and HSP) and identified the motifs of five CSBs in the mitochondrial displacement loop (D-loop) regions of 52 mammals. The conserved arrangement of these five CSBs in 17 primates inspired us to investigate the function of the mtDNA D-loop, which has been puzzling scientists for more than 50 years. We found that 5 sRNAs of MDL1AS control the expression levels of mitochondrial genes as a whole by a negative feedback mechanism. Thus, the precise annotations of three CSBs (CSB2, LSP and HSP) in more species will help to understand the function of the mtDNA D-loop. The precision annotation of animal mitochondrial genomes also provides abundant information for studying the molecular phylogenetics and evolution of animals.

bioinformatics↗

bioRxiv2019

SINATRA: A Sub-Image Analysis Pipeline for Selecting Features that Differentiate Classes of 3D Shapes

The recent curation of large-scale databases with 3D surface scans of shapes has motivated the development of tools that better detect global patterns in morphological variation. Studies which focus on identifying differences between shapes have been limited to simple pairwise comparisons and rely on pre-specified landmarks (that are often known). We present SINATRA: the first statistical pipeline for analyzing collections of shapes without requiring any correspondences. Our novel algorithm takes in two classes of shapes and highlights the physical features that best describe the variation between them. We use a rigorous simulation framework to assess our approach. Lastly, as a case study, we use SINATRA to analyze mandibular molars from four different suborders of primates and demonstrate its ability recover known morphometric variation across phylogenies.

bioinformatics↗

bioRxiv2019

Deep neural network affinity model for BACE inhibitors in D3R Grand Challenge 4

Drug Design Data Resource (D3R) Grand Challenge 4 (GC4) offered a unique opportunity for designing and testing novel methodology for accurate docking and affinity prediction of ligands in an open and blinded manner. We participated in the beta-secretase 1 (BACE) Subchallenge which is comprised of cross-docking and redocking of 20 macrocyclic ligands to BACE and predicting binding affinity for 154 macrocyclic ligands. For this challenge, we developed machine learning models trained specifically on BACE. We developed a deep neural network (DNN) model that used a combination of both structure and ligand-based features that outperformed simpler machine learning models. According to the results released by D3R, we achieved a Spearmans rank correlation coefficient of 0.43(7) for predicting the affinity of 154 ligands. We describe the formulation of our machine learning strategy in detail. We compared the performance of DNN with linear regression, random forest, and support vector machines using ligand-based, structure-based, and combining both ligand and structure-based features. We compared different structures for our DNN and found that performance was highly dependent on fine optimization of the L2 regularization hyperparameter, alpha. We also developed a novel metric of ligand three-dimensional similarity inspired by crystallographic difference density maps to match ligands without crystal structures to similar ligands with known crystal structures. This report demonstrates that detailed parameterization, careful data training and implementation, and extensive feature analysis are necessary to obtain strong performance with more complex machine learning methods. Post hoc analysis shows that scoring functions based only on ligand features are competitive with those also using structural features. Our DNN approach tied for fifth in predicting BACE-ligand binding affinities.

bioinformatics↗

bioRxiv2019

Discovery and Multi-center Verification of Prostate Cancer Protein Biomarkers using Single-shot Short Gradient Microflow SWATH and MRMHR Mass Spectrometry

We report and evaluated a microflow, single-shot, short gradient SWATH MS method intended to accelerate the discovery and verification of protein biomarkers in clinical specimens. The method uses 15-min gradient microflow-LC peptide separation, an optimized SWATH MS window configuration and OpenSWATH software for data analysis.\n\nWe applied the method to a cohort 204 of FFPE prostate tissue samples from 58 prostate cancer patients and 10 prostatic hyperplasia patients. Altogether we identified 27,976 proteotypic peptides and 4,043 SwissProt proteins from these 204 samples. Compared to a reference SWATH method with 2-hour gradient the accelerated method consumed only 27% instrument time, quantified 80% proteins and showed reduced batch effects. 3,800 proteins were quantified by both methods in two different instruments with relatively high consistency (r = 0.77). 75 proteins detected by the accelerated method with differential abundance between clinical groups were selected for further validation. A shortlist of 134 selected peptide precursors from the 75 proteins were analyzed using MRM-HR, exhibiting high quantitative consistency with the 15-min SWATH method (r = 0.89) in the same sample set. We further verified the capacity of these 75 proteins in separating benign and malignant tissues (AUC = 0.99) in an independent prostate cancer cohort (n=154).\n\nOverall our data show that the single-shot short gradient microflow-LC SWATH MS method achieved about 4-fold acceleration of data acquisition with reduced batch effect and a moderate level of protein attrition compared to a standard SWATH acquisition method. Finally, the results showed comparable ability to separate clinical groups.

cancer biology↗

bioRxiv2019

Comprehensive characterisation of molecular host-pathogen interactions in influenza A virus-infected human macrophages

Macrophages in the lung detect and respond to influenza A virus (IAV), determining the nature of the immune response. Using terminal depth 5-RNA sequencing (CAGE) we quantify transcriptional activity of both host and pathogen over a 24-hour timecourse of IAV infection in primary human monocyte-derived macrophages (MDM). We use a systems approach to describe the transcriptional landscape of the host response to IAV contrasted with bacterial lipopolysaccharide treated MDMs, observing a failure of IAV-treated MDMs to induce feedback inhibitors of inflammation. Systematic comparison of host RNA sequences incorporated into viral mRNA (\"snatched\") against a complete survey of background RNA in the host cell enables an unbiased quantification of over-represented features of snatched host RNAs. We detect preferential snatching of RNAs associated with snRNA transcription and demonstrate that cap-snatching avoids transcripts encoding host ribosomal proteins, which are required by IAV for replication.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=177 SRC=\"FIGDIR/small/670919v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (34K):\norg.highwire.dtl.DTLVardef@b05478org.highwire.dtl.DTLVardef@79a519org.highwire.dtl.DTLVardef@462739org.highwire.dtl.DTLVardef@1b91eb6_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical Abstract(A) Overview of bioinformatics pipeline. (B) Host gene expression reveals that human macrophages exposed to IAV exhibit sustained production of key inflammatory mediators and failure to induce expression of feedback inhibitors of inflammation. (C) Unbiased comparison with total background RNA expression demonstrates that IAV cap-snatching has a strong preference for, and aversion to, different groups of host transcripts.

immunology↗

bioRxiv2019

DNA Punch Cards: Encoding Data on Native DNA Sequences via Topological Modifications

Synthetic DNA-based data storage systems have received significant attention due to the promise of ultrahigh storage density and long-term stability. However, all platforms proposed so far suffer from high cost, read-write latency and error-rates that render them noncompetitive with modern optical and magnetic storage devices. One means to avoid synthesizing DNA and to reduce the system error-rates is to use readily available native DNA. As the symbol/nucleotide content of native DNA is fixed, one may adopt an alternative recording strategy that modifies the DNA topology to encode desired information. Here, we report the first macromolecular storage paradigm in which data is written in the form of "nicks (punches)" at predetermined positions on the sugar-phosphate backbone of native dsDNA. The platform accommodates parallel nicking on multiple "orthogonal" genomic DNA fragments and paired nicking and disassociation for creating "toehold" regions that enable single-bit random access and strand displacement in-memory computations. As a proof of concept, we used the programmable restriction enzyme Pyrococcus furiosus Argonaute to punch two files into the PCR products of Escherichia coli genomic DNA. The encoded data is accurately reconstructed through high-throughput sequencing and read alignment.

synthetic biology↗