Biology subjects

Chen, W.

Publications and source records attributed to Chen, W..

At least 595 records · Page 33Linked to original sources

bioRxiv2018

miR-263b controls circadian rhythms and structural plasticity of small ventral lateral neurons by inhibition of Beadex

Circadian clocks drive rhythmic physiology and behavior to allow adaption to daily environmental changes. In Drosophila, the small ventral lateral neurons (sLNvs) are the master pacemakers that control circadian rhythms. Circadian changes are observed in the dorsal axonal projections of the sLNvs, but their physiological importance and the underlying mechanism are unclear. Here we identified miR-263b as an important regulator of circadian rhythms in Drosophila. Flies depleted of miR-263b (miR-263bKO) exhibited dramatically impaired rhythms under constant darkness. Indeed, miR-263b is rhythmically expressed and controls circadian output by affecting the structural plasticity of sLNvs through inhibition of expression of the LIM-only protein Beadex (Bx). The misexpression of Bx in flies phenocopied miR-263bKO in behavior and molecular characteristics. In addition, the circadian phenotypes of miR-263bKO were recapitulated by mutating the miR-263b binding sites in the Bx 3'UTR. Together, these results establish miR-263b as an important regulator of circadian locomotor behavior.

neuroscience↗

bioRxiv2018

Sequencing of Panax notoginseng genome reveals genes involved in disease resistance and ginsenoside biosynthesis

Panax notoginseng is a traditional Chinese herb with high medicinal and economic value. There has been considerable research on the pharmacological activities of ginsenosides contained in Panax spp.; however, very little is known about the ginsenoside biosynthetic pathway. We reported the first de novo genome of 2.36 Gb of sequences from P. notoginseng with 35,451 protein-encoding genes. Compared to other plants, we found notable gene family contraction of disease-resistance genes in P. notoginseng, but notable expansion for several ATP-binding cassette (ABC) transporter subfamilies, such as the Gpdr subfamily, indicating that ABCs might be an additional mechanism for the plant to cope with biotic stress. Combining eight transcriptomes of roots and aerial parts, we identified several key genes, their transcription factor binding sites and all their family members involved in the synthesis pathway of ginsenosides in P. notoginseng, including dammarenediol synthase, CYP716 and UGT71. The complete genome analysis of P. notoginseng, the first in genus Panax, will serve as an important reference sequence for improving breeding and cultivation of this important nutraceutical and medicinal but vulnerable plant species.

genomics↗

bioRxiv2018

Duplications and functional specialization force distinct evolution of isoflavonoid biosynthetic genes in legumes

Isoflavonoids are specialized plant metabolites, almost exclusive to legumes, and synthesized by the phenylpropanoid pathway. Leguminous plants produce 5-deoxyflavonoids and 5-deoxyisoflavonoids that act in symbiosis with nitrogen-fixing bacteria and involved in plant pathogen and stress response. However, little is known about evolutional origin of legume-specific isoflavonoid biosynthesis pathway. Here, we explored the genome-wide analysis of key genes: chalcone synthase (CHS), chalcone reductase (CHR), isoflavone synthase (IFS) and isoflavone reductase (IFR), encoding enzymes involved in the biosynthesis of (iso) flavonoids in legumes and nonlegumes. Among them, CHS, CHR and IFR comprise multigene families, underling the significant role of gene duplication in the evolutionary. Most duplications of CHS were highly the conventional leguminous type, whereas some were grouped with nonleguminous CHS genes. We also found that CHR homologs in soybean and Sesbania rostrata previously reported were ambiguous and should be re-identified. Phylogenetic analysis and protein sequences alignment indicated that IFSs in legumes are highly conserved. Intriguingly, unlike other IFRs in legumes, IFR-like homologs in Sophora flavescens and Lupinus angustifolius shared high sequence similarity and protein structures with homologs in nonlegumes. Overall, these results offer reasonable gene annotations and comparative analysis and also provided a glimpse into evolutional route of legume-specific isoflavonoid biosynthesis.\n\nHighlightIsoflavonoids are specialized plant metabolites, almost exclusive to legumes. We firstly provide evidence that evolutional origin of legume-specific isoflavonoid biosynthesis may be driven by gene duplications and functional specialization.

genomics↗

bioRxiv2018

Radiogenomics-based Risk Prediction of Glioblastoma Multiforme with Clinical Relevance

GBM is the most common and aggressive primary brain tumor. Although the TMZ-based radiochemotherapy improves overall GBM patients survival, it also increases the frequency of false positive post-treatment magnetic resonance imaging (MRI) assessments for tumor progression. Pseudoprogression is a treatment-related reaction with an increase in contrast-enhancing lesion size at the tumor site or resection margins which mimics tumor recurrence on MRI. Accurate and reliable prognostication of GBM progression is urgently needed in the clinical management of GBM patients. Clinical data analysis indicates that the patients with PsP had superior overall and progression-free survival rates. In this study, we aimed to develop a prognostic model to evaluate tumor progression potential of GBM patients following standard therapies. We applied a dictionary learning scheme to obtain imaging features of GBM patients with PsP or TTP from the Wake dataset. Based on these radiographic features, we then conducted radiogenomics analysis to identify the significantly associated genes. These significantly associated genes were then used as features to construct a 2YS logistic regression model. GBM patients were classified into low-and high-survival risk groups based on the individual 2YS scores derived from this model. We tested our model using an independent TCGA dataset and found that 2YS scores were significantly associated with the patients overall survival. We further used two cohorts of the TCGA data to train and test our model. Our results show that 2YS scores-based classification results from the training and testing TGCA datasets were significantly associated with the overall survival of patients. We also analyzed the survival prediction ability of other clinical factors (gender, age, KPS, normal cell ratio) and found that these factors were not related or weakly correlated with patients survival. Overall, our studies have demonstrated the effectiveness and robustness of the 2YS model in predicting clinical outcomes of GBM patients after standard therapies.

bioinformatics↗

bioRxiv2018

The Mechanical of Organic Acids Secreted by Roots of Tartary Buckwheat under the Effects of Low Nitrogen Stress

A pot experiment was conducted to study the effects of two different low nitrogen tolerant tartary buckwheat varieties (Diqing buckwheat (DQ, low nitrogen resistance) and Heifeng 1 (HF, low nitrogen sensitive) response mechanism of organic acids to low nitrogen stress. The results showed that the soil moisture of HF and DQ under low nitrogen treatment decreased 24.2% and 14.32%, respectively when compared with normal nitrogen treatment, and the water consumption of DQ was significantly higher than that of HF at seedling stage. Under low nitrogen treatment, the soil pH value of DQ was 1.44% and 8.44% lower than that of HF at seedling and flowering stages, respectively, the content of NH4+ in DQ soil was 8.2% lower than that of HF at maturity stage, the content of NO3- was significantly higher than that HF 49.2%, 12.9%, and 16.6% in each growth period, respectively. Split plot analysis showed that nitrogen treatment significantly affected the organic acids content in the soil of the buckwheat. The secretion content of organic acids are different among buckwheat cultivars under low nitrogen stress. In the soil of DQ, the content of malonic acid was higher than that of HF by 34.39% at maturity stage; the content of oxalic acid was respectively higher than that of HF by 24.86% and 24.52% at seedling and flowering stages; the content of propionic acid was significantly higher than that of HF by 7.36%, 9.44% and23.47% in each growth period, respectively; and tartaric acid acetic acid also showed the same trend at flowering and maturity stages. In summary, tartary buckwheat may regulate the nutrient availability of rhizosphere soil through the secretion of organic acids in the root system to cope with the low nitrogen stress environment. For the cultivation of tartary buckwheat on poor soil should consider the differences cultivaring barren resistance varieties to increase efficiency in the future.

plant biology↗

bioRxiv2018

Identification of pathogens in culture-negative infective endocarditis with metagenomic analysis

Pathogens identification is critical for the proper diagnosis and precise treatment of infective endocarditis. Although blood and valve cultures are the gold standard for IE pathogens detection, many cases are culture-negative, especially in patients who had received long-term antibiotic treatment, and precise diagnosis has therefore become a major challenge in the clinic. Metagenomic sequencing can provide both information on the pathogenic strain and the antibiotic susceptibility profile of patient samples without culturing, offering a powerful method to deal with culture-negative cases. In this work, we assessed the feasibility of a metagenomic approach to detect the causative pathogens in resected valves from IE patients.\n\nUsing our in-house developed bioinformatics pipeline, we analyzed the sequencing results generated from both next-generation sequencing and Oxford Nanopore Technologies MinION nanopore sequencing for the direct identification of pathogens from the resected valves of seven clinically culture-negative IE patients according to the modified Duke criteria. Moreover, we were able to simultaneously characterize respective antimicrobial resistance features. This provides clinicians with valuable information to diagnose and treat IE patients after valve replacement surgery.

microbiology↗

bioRxiv2018

Identification of key genes related to dexamethasone-resistance in acute lymphoblastic leukemia

Drug resistance is the main cause of poor chemotherapy response in acute leukemia. Despite the extensive use of dexamethasone(DEX) in the treatment of acute lymphoblastic leukemia for many years, the mechanisms of dexamethasone - resistance has not been fully understood. We choose GSE94302 from GEO database aiming to identify key genes that contribute to the DEX resistance in acute lymphoblastic leukemia. Differentially expressed gene(DEGs) are selected by using GEO2R tools. A total of 837 DEGs were picked out, including 472 up-regulated and 365 down-regulated DEGs. All the DEGs were underwent gene ontology(GO) analysis and Kyoto Encyclopedia of Gene and Genome(KEGG) pathway analysis. In addition, the DEGs-encoded protein-protein interaction (PPI) was screened by using Cytoscape and Search Tool for the Retrieval of Interacting Genes(STRING). Total 20 genes were found as key genes related to DEX resistance with high degree of connectivity, including CDK1, PCNA, CCNB1, MYC, KPNA2, AURKA, NDC80, HSPA4, KIF11, UBE2C, PIK3CG, CD44, CD19, STAT1, DDX41, LYN, BCR, CD48, JAK1 and ITGB1. They could be used as biomarkers to identify the DEX-resistant acute lymphoblastic leukemia.

bioinformatics↗

bioRxiv2018

Pleotropic effects of PPARD accelerate colorectal tumor progression and invasion

Colorectal carcinogenesis (CRC) progression requires additional molecular mechanisms to APC mutations/aberrant {beta}-catenin signaling. PPARD is a druggable ligand-activated nuclear receptor that regulates essential genes involved in cell fate. PPARD is upregulated in intestinal epithelial cells (IECs) of human colorectal adenomas and adenocarcinomas. The mechanistic significance of PPARD upregulation in CRC remains unknown. Here we show that targeted PPARD overexpression in IECs of mice strongly augmented {beta}-catenin activation via BMP7/TAK1 signaling, promoted intestinal tumorigenesis in Apcmin mice, and accelerated CRC progression and invasiveness in mice with IEC-targeted Apc{Delta}580 mutation. Human CRC invasive fronts had higher PPARD expression than their paired adenomas. A PPARD agonist (GW501516) enhanced APC{Delta}580 mutation-driven CRC, while a PPARD antagonist (GSK3787) suppressed it. Functional proteomics analyses and subsequent validation studies uncovered PPARD upregulation of multiple pro-invasive pathways that drive CRC progression (e.g. PDGFR{beta}, AKT1, CDK1 and EIF4G1). Our results identify novel mechanisms by which PPARD promotes CRC invasiveness and provide the rational for the development of PPARD antagonists to suppress CRC.

cancer biology↗

bioRxiv2018

Discovery of New CDK8 ligands with a Novel Virtual Drug Screening Tool

Selective inhibition of CDK8 could be a promising strategy for reducing mitogenic signals in cancer cells with reduced toxic effects on normal cells. As compared with type I ligands, binding of a type II compound often achieves longer residence time. We developed a novel virtual drug screening package which takes advantage of two energy evaluation methods: Superposition and Single-Point Energy Evaluation, and VM2 free energy calculation, and applied it to the discovery of new CDK8 type II ligands. In this research we analyzed binding thermodynamics of 11 published CDK8 type II ligands, and extracted the key binding information to assist virtual drug screening for new ligands. The free energy and MD calculations on the reference CDK8-ligand complexes revealed the important factors in the binding. The urea moiety was found to be the critical structural contributor of the reference ligands. Starting with the urea moiety we implemented virtual drug screening and singled out three compounds for bio-assay testing. The ranking from the experimental result for the three compounds is completely consistent with the predicted rankings by both energy evaluation methods. A potent drug-like compound was discovered to have a Kd value of 42.5 nM with CDK8, which is comparable to the most potent reference ligands and provided a good starting point to design and synthesize a series of highly selective and potent CDK8 ligands. Therefore, our novel virtual drug screening package is accurate and efficient enough to be used in drug design projects. We believe this work has significant impact to the field of drug discovery.

bioinformatics↗

bioRxiv2018

Reduced but not Enhanced Default Mode Network Functional Connectivity in Major Depressive Disorder: Evidence from 25 Cohorts in the REST-meta-MDD Project

Major Depressive Disorder (MDD) is common and disabling, but its neural pathophysiology remains unclear. Functional brain network studies in MDD have largely had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. The 25 research groups in China composing the REST-meta-MDD Project contributed R-fMRI data of 1,300 patients with MDD and 1,128 normal controls (NCs). The data were preprocessed locally with a standardized protocol prior to aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to show increased FC in MDD. We found decreased instead of increased DMN FC when comparing 848 MDDs with 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naive MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDDs. Exploratory analyses also revealed alterations of local intrinsic activity in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates treatment response. This manuscript announces the publicly available resting-state fMRI indices of the REST-meta-MDD consortium shared via the R-fMRI Maps Project.\n\nSIGNIFICANCE STATEMENTFunctional connectivity within the default mode network in major depressive disorder patients has been frequently reported abnormal but with contradicting directions in previous small sample size studies. By creating the REST-meta-MDD consortium containing neuroimaging data of 1,300 depressed patients and 1,128 normal controls from 25 research groups in China, we found decreased default mode network functional connectivity in depressed patients, driven by patients with recurrent depression, and associated with current medication treatment but not with disease duration. These findings suggest that default mode network functional connectivity remains a prime target for understanding the pathophysiology of depression, with particular relevance to revealing mechanisms of effective treatments.

neuroscience↗

bioRxiv2018

SupportNet: a novel incremental learning framework through deep learning and support data

MotivationIn most biological data sets, the amount of data is regularly growing and the number of classes is continuously increasing. To deal with the new data from the new classes, one approach is to train a classification model, e.g., a deep learning model, from scratch based on both old and new data. This approach is highly computationally costly and the extracted features are likely very different from the ones extracted by the model trained on the old data alone, which leads to poor model robustness. Another approach is to fine tune the trained model from the old data on the new data. However, this approach often does not have the ability to learn new knowledge without forgetting the previously learned knowledge, which is known as the catastrophic forgetting problem. To our knowledge, this problem has not been studied in the field of bioinformatics despite its existence in many bioinformatic problems.\n\nResultsHere we propose a novel method, SupportNet, to solve the catastrophic forgetting problem efficiently and effectively. SupportNet combines the strength of deep learning and support vector machine (SVM), where SVM is used to identify the support data from the old data, which are fed to the deep learning model together with the new data for further training so that the model can review the essential information of the old data when learning the new information. Two powerful consolidation regularizers are applied to ensure the robustness of the learned model. Comprehensive experiments on various tasks, including enzyme function prediction, subcellular structure classification and breast tumor classification, show that SupportNet drastically outperforms the state-of-the-art incremental learning methods and reaches similar performance as the deep learning model trained from scratch on both old and new data.\n\nAvailabilityOur program is accessible at: https://github.com/lykaust15/SupportNet.

bioinformatics↗

bioRxiv2018

A direct comparison of four high risk human papilloma virus tests versus the cobas test for detecting cervical intraepithelial neoplasia and cervical cancer

This study is to evaluate performances and genotyping capabilities of four human papilloma virus (HR-HPV) tests based on real-time polymerase chain reaction (PCR) technology platforms compared with the cobas test. Discordant results were further analyzed using INNO-LiPA HPV genotyping test, the gold standard laboratory test to determine presence and type of HPV infection. Over 200 samples from Hospital patients were collected and analyzed using five HR-HPV tests. Women with positive test results were referred directly to colposcopy. If a positive result was returned, biopsies were administered for pathological classification. Clinical performances and genotyping capabilities between the four HR-HPV and cobas tests were compared and contrasted. High levels of agreement were observed, though all HR-HPV tests presented discrepancies compared with the cobas test. Cervical intraepithelial neoplasia Grade 2 or higher lesions (CIN2+) was set as the threshold, and all five tests performed with equally high sensitivity. Lower levels of specificity were observed across all five tests. Results suggest the four HR-HPV tests analyzed are as effective as the cobas test in genotyping capacities and diagnosing CIN. Therefore, these test kits should be used for HPV screening, especially in developing nations because they are cost effective and reliable. Minor discrepancies between tests are generally unavoidable though this may add complexity to the clinical decision-making process. As such, we recommend that efforts be made to standardize HPV genotyping tests as well as to optimize clinical sensitivity and specificity. Focusing on these issues will drive the development of HPV detection techniques, therefore save lives.

epidemiology↗

bioRxiv2018

Histone deacetylase HDA19 affects cortical cell fate by interacting with SCARECROW in the Arabidopsis root

Abstract/SummaryThe Arabidopsis root epidermis is a simple model for investigating cell fate specification and pattern formation. In addition to regulatory networks consisting of transcription factors, histone deacetylases are also involved in the cellular patterning process. Here we report HDA19 affects the root epidermal cellular pattern through regulation of cortical cell fate by interacting with SCARECROW. This work reveals two new components in cortical cell specification and uncovers a new facet of SCR function.

plant biology↗

bioRxiv2018

LCA robustly reveals subtle diversity in large-scale single-cell RNA-seq data

Single-cell RNA sequencing has emerged as a powerful tool for characterizing the cell-to-cell variation and dynamics. We present Latent Cellular Analysis (LCA), a machine learning-based analytical pipeline that features a dual-space model search with inference of latent cellular states, control of technical variations, cosine similarity measurement, and spectral clustering. LCA has proved to be robust, accurate, scalable, and powerful in revealing subtle diversity in cell populations.

bioinformatics↗

bioRxiv2018

RNAs as proximity labeling media for identifying nuclear speckle positions relative to the genome

Nuclear speckles are interchromatin structures enriched in RNA splicing factors. Determining their relative positions with respect to the folded nuclear genome could provide critical information on co-and post-transcriptional regulation of gene expression. However, it remains challenging to identify which parts of the nuclear genome are in proximity to nuclear speckles, due to physical separation between nuclear speckle cores and chromatin. We hypothesized that noncoding RNAs including small nuclear RNAs, 7SK and Malat1, which accumulate at the periphery of nuclear speckles (nsaRNA, nuclear speckle associated RNA), may extend to sufficient proximity to the nuclear genome. Leveraging a transcriptome-genome interaction assay (MARGI), we identified nsaRNA-interacting genomic sequences, which exhibited clustering patterns (nsaPeaks) in the genome, suggesting existence of relatively stable interaction sites for nsaRNAs in nuclear genome. Posttranscriptional pre-mRNAs, which are known to be clustered to nuclear speckles, exhibited proximity to nsaPeaks but rarely to other genomic regions. Furthermore, CDK9 proteins that localize to the vicinity of nuclear speckles produced ChIP-seq peaks that overlapped with nsaPeaks. Our combined DNA FISH and immunofluorescence analysis in 182 single cells revealed a 3-fold increase in odds for nuclear speckles to localize near an nsaPeak than its neighboring genomic sequence. These data suggest a model that nsaRNAs locate in sufficient proximity to nuclear genome and leave identifiable genomic footprints, thus revealing the parts of genome proximal to nuclear speckles.

bioinformatics↗

bioRxiv2018

Polygenic risk scores for major depressive disorder and neuroticism as predictors of antidepressant response: meta-analysis of three treatment cohorts.

There are currently no reliable approaches for correctly identifying which patients with major depressive disorder (MDD) will respond well to antidepressant therapy. However, recent genetic advances suggest that Polygenic Risk Scores (PRS) could allow MDD patients to be stratified for antidepressant response. We used PRS for MDD and PRS for neuroticism as putative predictors of antidepressant response within three treatment cohorts: The Genome-based Therapeutic Drugs for Depression (GENDEP) cohort, and 2 sub-cohorts from the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomics Study PRGN-AMPS (total patient number = 783). Results across cohorts were combined via meta-analysis within a random effects model. Overall, PRS for MDD and neuroticism did not significantly predict antidepressant response but there was a consistent direction of effect, whereby greater genetic loading for both MDD (best MDD result, p < 5*10-5 MDD-PRS at 4 weeks, {beta} = -0.019, S.E = 0.008, p = 0.01) and neuroticism (best neuroticism result, p < 0.1 neuroticism-PRS at 8 weeks, {beta} = -0.017, S.E = 0.008, p = 0.03) were associated with less favourable response. We conclude that the PRS approach may offer some promise for treatment stratification in MDD and should now be assessed within larger clinical cohorts.

genetics↗

bioRxiv2018

Profiling copy number alterations in cell-free tumour DNA using a single-reference

BackgroundThe accurate detection of copy number alterations from the analysis of circulating cell free tumour DNA (ctDNA) in blood is essential to realising the potential of liquid biopsies. However, currently available approaches require a large number of plasma samples from healthy individuals, sequenced using the same platform and protocols to act as a reference panel. Obtaining this reference panel can be challenging, prohibitively expensive and limits the ability to migrate to improved sequencing platforms and improved protocols.\n\nMethodsWe developed qCNV and sCNA-seq, two distinct tools that together provide a new approach for profiling somatic copy number alterations (sCNA) through the analysis of cell free DNA (cfDNA) without a reference panel. Our approach was designed to identify sCNA from cfDNA through the analysis of a single plasma sample and a matched normal DNA sample -both of which can be obtained from the same blood draw. qCNV is an efficient method for extracting read-depth from BAM files and sCNA-seq is a method that uses a probabilistic model of read depth to infer the copy number segmentation of the tumour. We compared the results from our pipeline to the established copy number profile of a cell-line, as well as the results from the plasma-Seq analysis of cfDNA-like mixtures and real, clinical data-sets.\n\nResultsWith a single, unmatched, germline reference sample, our pipeline recapitulated the known copy number profile of a cell-line and demonstrated similar results to those obtained from plasma-Seq. With less than 1X genome coverage, our approach identified clinically relevant sCNA in samples with as little as 20 % tumour DNA. When applied to plasma samples from cancer patients, our pipeline identified clinically significant mutations.\n\nConclusionsThese results show it is possible to identify therapeutically-relevant copy number mutations from plasma samples without the need to generate a reference panel from a large number of healthy individuals. Together with the range of sequencing platforms supported by our qCNV+sCNA-Seq pipeline, as well as the Galaxy implementation of this solution, this pipeline makes cfDNA profiling more accessible and makes it easier to identify sCNA from the plasma of cancer patients.

bioinformatics↗

bioRxiv2018

Recombinant expression of Proteorhodopsin and biofilm regulators in Escherichia coli for nanoparticle binding and removal in a wastewater treatment model

The small size of nanoparticles is both an advantage and a problem. Their high surface-area-to-volume ratio enables novel medical, industrial, and commercial applications. However, their small size also allows them to evade conventional filtration during water treatment, posing health risks to humans, plants, and aquatic life. This project aims to remove nanoparticles during wastewater treatment using genetically modified Escherichia coli in two ways: 1) binding citrate-capped nanoparticles with the membrane protein Proteorhodopsin, and 2) trapping nanoparticles using Escherichia coli biofilm produced by overexpressing two regulators: OmpR234 and CsgD. We demonstrate experimentally that Escherichia coli expressing Proteorhodopsin binds to 60 nm citrate-capped silver nanoparticles. We also successfully upregulate biofilm production and show that Escherichia coli biofilms are able to trap 30 nm gold particles. Finally, both Proteorhodopsin and biofilm approaches are able to bind and remove nanoparticles in simulated wastewater treatment tanks. We envision integrating our trapping system in both rural and urban wastewater treatment plants to efficiently capture all nanoparticles before treated water is released into the environment.\n\nFinancial DisclosureThis work was funded by the Taipei American School. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\nCompeting InterestsThe authors have declared that no competing interests exist.\n\nEthics StatementN/A\n\nData AvailabilityYes - all data are fully available without restriction. Sequences for the plasmids used in this study are available through the Registry of Standard Biological Parts. Links to raw data are included in Supplementary Information.

synthetic biology↗