Biology subjects

Zhang, S.

Publications and source records attributed to Zhang, S..

At least 595 records · Page 33Linked to original sources

bioRxiv2024

Beige adipose tissue-derived extracellular vesicles: a potent metabolic regulator and a novel remedy for nonalcoholic fatty liver disease

Adipose tissue (AT) is an essential metabolic and endocrine organ, which are categorized into the white adipose tissue (WAT) and the brown adipose tissue (BAT), as well as the beige adipose tissue (BeAT) that derives from WAT browning. Notably, extracellular vesicles (EVs), especially tissue-produced EVs, have been recognized to be critical players in multiple physiological and pathophysiological settings and provide efficient strategy for disease treatment. However, little is known about the BeAT-derived EVs (BeEVs). In this study, we induced BeEV formation by cold stimulation and extracted EVs from three kinds of AT via enzyme digestion combined with gradient centrifugation. The isolated BeEVs possess typical morphological, structural and marker characteristics of EVs. Proteomics analysis further demonstrated that the BeEVs hold a distinct protein profile while are enriched with multiple metabolic regulatory proteins. Importantly, systemic injection of BeEVs into mice improved metabolic dysfunction in a nonalcoholic fatty liver disease (NAFLD) model induced by high-fat diet (HFD). Moreover, we demonstrated that the BeEVs alleviated liver steatosis via decreasing the lipogenesis. These findings promote the understanding of AT-EVs and shed light on the isolation, identification and applications of BeEVs as a potent metabolic regulator and novel remedy for metabolic diseases.

cell biology↗

bioRxiv2023

Thermo-Responsive Polymers Targeting Inflammation in Murine Colitis

Targeting the site of inflammation is an ideal approach for treating inflammatory bowel disease (IBD). Inflammation targeting enables maximal drug-on-target effects while minimizing off-target side effects. Negatively charged drug carriers have been shown to facilitate drug delivery to inflamed colon mucosa after local administration. To modulate the negative charges and integrate responsiveness to stimuli, here we describe thermo-responsive, inflammation-targeting (TRIT) hydrogels based on functionalized poly(N-isopropylacrylamide-co-methacrylic acid) (PNIPAM-MAA). We show that both chemical modification types and polymer molecular weights affect the resultant microgels adhesion to the inflamed colon in dextran sulfate sodium (DSS)-induced murine colitis in vivo. Further, we quantified the correlations between microgels adhesion and colitis severity for individual mice, demonstrating that the microgels adhesion correlated directly with weight loss percentage in DSS-treated mice. By exploiting charge-mediated interaction and thermo-responsiveness, TRIT hydrogels represent a promising strategy to target inflamed colon mucosa as a drug delivery platform for colonic IBD treatment. TeaserThis study developed thermo-responsive, inflammation-targeting (TRIT) hydrogels that harness charge-mediated interaction and sol-to-gel transition to target inflamed colon mucosa as a new approach for treating inflammatory bowel disease.

bioengineering↗

bioRxiv2023

A comparative analysis of planarian genomes reveals regulatory conservation in the face of rapid structural divergence

The planarian Schmidtea mediterranea can regenerate its entire body from small tissue fragments and is studied as regeneration model species. The assembly and functional analysis of planarian genomes has proven challenging due its high A/T content (70% A/T), repetitive nature, and limited transferability of routine laboratory protocols due to their divergent biochemistry. Only few and often fragmented genome assemblies are currently available, and open challenges include the provision of well-annotated chromosome-scale reference assemblies of the model species and other planarians for a comparative genome evolution perspective. Here we report a haplotype-phased, chromosome-scale genome assembly and high-quality gene annotations of the sexual S2 strain of S. mediterranea and provide putative regulatory region annotations via optimized ATAC-seq and ChIP-seq protocols. To additionally leverage sequence conservation for regulatory element annotations, we generated chromosome-scale genome assemblies and chromatin accessibility data for the three closest relatives of S. mediterranea: S. polychroa, S. nova, and S. lugubris. We find substantial divergence in protein-coding sequences and regulatory regions, yet reveal remarkable conservation in ChIP-mark bearing open chromatin regions identified as promoters and enhancers in S. mediterranea. The resulting high-confidence set of evolutionary conserved enhancers and promoters provides a valuable resource for the analysis of gene regulatory circuits and their evolution within the taxon. In addition, our four chromosome-scale genome assemblies provide a first comparative perspective on planarian genome evolution. Our analyses reveal frequent retrotransposon-associated chromosomal inversions and inter-chromosomal translocations that lead to a degradation of synteny across the genus. Interestingly, we further find independent and near-complete losses of the ancestral metazoan synteny across Schmidtea and two other flatworm groups, indicating that platyhelminth genomes largely evolve without syntenic constraints. Our work provides valuable genome resources for the planarian research community and sets a foundation for the comparative genomics of planarians. We reveal a contrast between the fast structural evolution of planarian genomes and the conservation of their regulatory elements, suggesting a unique genome evolution in flatworms where gene positioning may not be essential.

genomics↗

bioRxiv2023

An Endogenous Aryl Hydrocarbon Receptor Ligand Induces Preeclampsia-like Phenotypes: Transcriptome, Phosphoproteome, and Cell Functions

BackgroundPreeclampsia (PE) is one hypertensive disorder and a leading cause of maternal and fetal mortality and morbidity during human pregnancy. Aryl hydrocarbon receptor (AhR) is a transcription factor, which regulates vascular functions. Exogenous and endogenous AhR ligands can induce hypertension in animals. However, if dysregulation of endogenous AhR ligands contributes to the pathophysiology of PE remains elusive. MethodsWe measured AhR activities in human maternal and umbilical vein sera. We also applied physiological, cellular, and molecular approaches to dissect the role of endogenous AhR ligands in vascular functions during pregnancy using pregnant rats and primary human umbilical vein endothelial cells (HUVECs) as models. ResultsPE elevated AhR activities in human umbilical vein sera. Exposure of pregnant rats to an endogenous AhR ligand, 2-(1H-indole-3-carbonyl)-thiazole-4-carboxylic acid methyl ester (ITE) increased blood pressure and proteinuria, while decreased uteroplacental blood flow and reduced fetal and placental weights, all of which are hallmarks of PE. ITE dampened vascular growth and fetal sex-specifically altered immune cell infiltration in rat placentas. ITE also decreased cell proliferation and cell monolayer integrity in HUVECs in vitro. RNA sequencing analysis revealed that ITE dysregulated transcriptome in rat placentas and HUVECs in a fetal sex-specific manner. Bottom-up phosphoproteomics showed that ITE disrupted phosphoproteome in HUVECs. These ITE-dysregulated genes and phosphoproteins were enriched in biological functions and pathways which are highly relevant to diseases of heart, liver, and kidney, vascular functions, inflammation responses, cell death, and kinase inhibition. ConclusionsDysregulation of endogenous AhR ligands during pregnancy may lead to the development of PE with underlying impaired vascular functions, fetal sex-specific immune cell infiltration and transcriptome, and phosphoproteome. Thus, this study has provided a novel mechanism for the development of PE and potentially other forms of hypertensive pregnancies. These AhR ligand-activated genes and phosphoproteins might represent promising therapeutic and fetal sex-specific targets for PE-impaired vascular functions.

pathology↗

bioRxiv2023

Site Effects in Multisite Fetal Brain MRI: Morphological Insights into Early Brain Development

BackgroundMultisite MRI studies have become prevalent given their advantage in revealing reliable biological or clinical findings. Adult and adolescent multisite studies have demonstrated inevitable site-related non-biological effects that introduce bias. However, the site effect on fetal brain MRI remains unknown. PurposeTo identify crucial acquisition factors affecting fetal brain structural measurements and developmental patterns, while assessing the effectiveness of existing harmonization methods in mitigating site effects. Materials and MethodsBetween May 2017 and March 2022, T2-weighted fast spin-echo sequences in-utero MRI were performed in healthy fetuses from prospectively recruited pregnant volunteers on four different scanners at four sites. A generalized additive model (GAM) was used to quantitatively assess site effects, including field strength (FS), manufacture (M), in-plane resolution (R), and slice thickness (ST), on subcortical volume and cortical morphological measurements, including cortical thickness, curvature, and sulcal depth. Growth models were selected to elucidate developmental trajectories of these morphological measurements. Welchs test was performed to evaluate the influence of site effects on developmental trajectories. ComBat-GAM harmonization method was applied to mitigate site-related biases. ResultsThe final analytic sample consisted of 340 MRI scans from 218 fetuses (mean gestational age, 30.1 weeks {+/-} 4.4 [range, 21.7-40 weeks]). GAM results showed that low FS and low spatial resolution led to overestimations in selected brain regions of subcortical volumes and cortical morphological measurements, and cortical measurements were more susceptible to site effects than subcortical volumes. Only the peak cortical thickness in developmental trajectories was significantly influenced by the effects of FS and R. Notably, ComBat-GAM harmonization effectively removed site effects while preserving developmental patterns. ConclusionOur findings pinpointed the key acquisition factors in in-utero fetal brain MRI and underscored the necessity of data harmonization when pooling multisite data for fetal brain morphology investigations.

bioengineering↗

bioRxiv2023

The E3 ubiquitin ligase RNF220 maintains hindbrain Hox expression patterns through regulation of WDR5 stability

The spatial and temporal linear expression of Hox genes establishes a regional Hox code, which is crucial for the antero-posterior (A-P) patterning, segmentation, and neuronal circuit development of the hindbrain. RNF220, an E3 ubiquitin ligase, is widely involved in neural development via targeting of multiple substrates. Here, we found that the expression of Hox genes in the pons was markedly up-regulated at the late developmental stage (post-embryonic day E15.5) in Rnf220-/- and Rnf220+/-mouse embryos. Single-nucleus RNA-seq analysis revealed different Hox de-repression profiles in different groups of neurons, including the pontine nuclei (PN). The Hox pattern was disrupted and the neural circuits were affected in the PN of Rnf220+/- mice. We showed that this phenomenon was mediated by WDR5, a key component of the TrxG complex, which can be polyubiquitinated and degraded by RNF220. Intrauterine injection of WDR5 inhibitor (WDR5-IN-4) and genetic ablation of Wdr5 in Rnf220+/- mice largely recovered the de-repressed Hox expression pattern in the hindbrain. In P19 embryonal carcinoma cells, the retinoic acid induced Hox expression was further stimulated by Rnf220 knockdown, which can also be rescued by Wdr5 knockdown. In short, our data suggest a new role of RNF220/WDR5 in Hox pattern maintenance and pons development in mice.

developmental biology↗

bioRxiv2023

CCT3 drives Sorafenib resistance by inhibiting TFRC-mediated iron uptake in HCC

Sorafenib is commonly utilized in the management of advanced hepatocellular carcinoma (HCC). However, its efficacy in extending patients survival is hindered by the development of drug resistance. By employing protein posttranslational modification (PTM) omics, including acetylome, phosphoproteome, and ubiquitinome, in conjunction with genome-wide CRISPR/Cas9 knockout library screening, we have successfully identified chaperonin containing TCP1 subunit 3 (CCT3) as a key factor contributing to Sorafenib resistance. Furthermore, we observed a reduction in the ubiquitination of CCT3 at lysine 21 (K21) subsequent to Sorafenib treatment. This study provides evidence that CCT3 hinders the recycling of transferrin receptor protein 1 (TFRC) by interacting with alpha-actinin-4 (ACTN4), which is influenced by K6-linked ubiquitination on K21. Depleting CCT3 increased the susceptibility of cells to Sorafenib-induced ferroptosis, while reintroducing CCT3 through transfection restored resistance to ferroptosis. Additionally, impairing ACTN4 or TFRC depletion compromised CCT3s ability to inhibit Sorafenib-induced ferroptosis. In summary, targeting CCT3 presents a potential strategy for overcoming Sorafenib resistance in HCC.

cancer biology↗

bioRxiv2023

A high-fidelity CRISPR-Cas13 system improves abnormalities associated with C9ORF72-linked ALS/FTD

An abnormal expansion of a GGGGCC hexanucleotide repeat in the C9ORF72 gene is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), two debilitating neurodegenerative disorders driven in part by gain-of-function mechanisms involving transcribed forms of the repeat expansion. By utilizing a Cas13 variant with reduced collateral effects, we developed a high-fidelity RNA-targeting CRISPR-based system for C9ORF72-linked ALS/FTD. When delivered to the brain of a transgenic rodent model, this Cas13-based platform effectively curbed the expression of the GGGGCC repeat-containing RNA without affecting normal C9ORF72 levels, which in turn decreased the formation of RNA foci and reversed transcriptional deficits. This high-fidelity Cas13 variant possessed improved transcriptome-wide specificity compared to its native form and mediated efficient targeting in motor neuron-like cells derived from a patient with ALS. Our results lay the foundation for the implementation of RNA-targeting CRISPR technologies for C9ORF72-linked ALS/FTD.

bioengineering↗

bioRxiv2023

A phosphorylation-dependent switch of the lysosomal V-ATPase assembly regulates α-synuclein clearance in glia

Glia serve as double-edged swords to modulate neuropathology in Parkinsons disease (PD), but how they react opposingly to be beneficial or detrimental under pathological conditions, like promoting or eliminating -synuclein (-syn) inclusions, remains elusive. Here we present evidence that dAuxilin (dAux), the Drosophila homolog of the PD risk factor Cyclin G-associated kinase (GAK), regulates the lysosomal degradation of -syn in glia. Lack of glial Gak/dAux increases the lysosome number and size, regulates lysosomal acidification and hydrolase activity, and ultimately blocks the degradation of substrates including -syn. Whereas -syn accumulated prominently in lysosomes devoid of glial dAux, levels of injected -syn preformed fibrils also further enhanced in the absence of microglial Gak. Mechanistically, dAux mediates phosphorylation at the serine 543 of Vha44, the V1C subunit of the vacuolar H+-ATPase (V-ATPase), regulates its assembly to control proper acidification of the lysosomal milieu. Expression of Vha44, but not the Vha44 variant lacking S543 phosphorylation, restores lysosome acidity, locomotor deficits, and DA neurodegeneration upon glial dAux depletion, linking this pathway to PD. Our findings identify a phosphorylation-dependent switch controlling the V-ATPase assembly for lysosomal -syn degradation in glia. Targeting the clearance of glial -syn inclusions via this lysosomal pathway could potentially be a therapeutical approach to ameliorate the disease progression in PD.

neuroscience↗

bioRxiv2023

Multilayer meta-matching: translating phenotypic prediction models from multiple datasets to small data

Resting-state functional connectivity (RSFC) is widely used to predict phenotypic traits in individuals. Large sample sizes can significantly improve prediction accuracies. However, for studies of certain clinical populations or focused neuroscience inquiries, small-scale datasets often remain a necessity. We have previously proposed a "meta-matching" approach to translate prediction models from large datasets to predict new phenotypes in small datasets. We demonstrated large improvement of meta-matching over classical kernel ridge regression (KRR) when translating models from a single source dataset (UK Biobank) to the Human Connectome Project Young Adults (HCP-YA) dataset. In the current study, we propose two meta-matching variants ("meta-matching with dataset stacking" and "multilayer meta-matching") to translate models from multiple source datasets across disparate sample sizes to predict new phenotypes in small target datasets. We evaluate both approaches by translating models trained from five source datasets (with sample sizes ranging from 862 participants to 36,834 participants) to predict phenotypes in the HCP-YA and HCP-Aging datasets. We find that multilayer meta-matching modestly outperforms meta-matching with dataset stacking. Both meta-matching variants perform better than the original "meta-matching with stacking" approach trained only on the UK Biobank. All meta-matching variants outperform classical KRR and transfer learning by a large margin. In fact, KRR is better than classical transfer learning when less than 50 participants are available for finetuning, suggesting the difficulty of classical transfer learning in the very small sample regime. The multilayer meta-matching model is publicly available at GITHUB_LINK.

neuroscience↗

bioRxiv2023

Spatially resolved molecular and cellular atlas of the mouse brain

A comprehensive atlas of genes, cell types, and their spatial distribution across a whole mammalian brain is fundamental for understanding function of the brain. Here, using snRNA-seq and Stereo-seq techniques, we generated a mouse brain atlas with spatial information for 308 cell clusters with single-cell resolution involving over 6 million cells as well as for 29,655 genes. We have identified new astrocyte clusters, and demonstrated that distinct cell clusters exhibit preference for cortical subregions. In addition, we identified 155 genes exhibiting regional specificity in the brainstem, and 513 long non-coding RNA exhibited regional specificity in the adult brain. Parcellation of brain regions based on spatial transcriptomic information showed large overlap with that by traditional method. Furthermore, we have uncovered 411 transcription factor regulons with spatiotemporal specificity during development. Thus, our study has discovered genes and regulon with spatiotemporal specificity, and provided a high-resolution spatial transcriptomic atlas of the mouse brain.

neuroscience↗

bioRxiv2023

TRAIL pathway suppression of cancer cell growth and immune cell-mediated tumor cell-killing in a senescent fibroblast-constructed tumor microenvironment

Cellular senescence and the associated secretory phenotype (SASP) promote cancer in the aging population. During aging or upon chemotherapy exposure, cellular and molecular changes occur in non-cancerous cells and alter responses to cancer therapy, primarily via modifications in the tumor microenvironment (TME) and immune response. Targeting senescent cells through removal, modulation of the SASP, or cellular reprogramming represent promising therapeutic avenues for treating cancer. We elucidate an interplay between cancer cells, immune cells, and senescent fibroblasts and describe the impact of fibroblast senescence on tumor growth and response to cancer therapy. Cytokine profiling reveals dynamic changes in SASP production during etoposide-induced senescence in IMR90 fibroblasts. We show that SASP is partially regulated by p21 (WAF1; CDKN1A), leading to the downregulation of anti-tumorigenic cytokines and upregulation of pro-tumorigenic cytokines. Senescent fibroblasts promote bystander cancer cell growth via a p21-driven SASP. These results provide strategies to target the p21-driven SASP in the TME during cancer therapy. Treatment with TRAIL or TRAIL-inducing Dordaviprone (TIC10/ONC201) reduces cell viability of tumor cells co-cultured with senescent or proliferating fibroblasts and promotes immune-mediated tumor cell-killing in co-culture with senescent IMR90 fibroblasts. ONC201 combined with senolytic drugs (e.g., Navitoclax, Lamivudine) synergizes towards tumor suppression. These results indicate that senolytic therapies may be combined with cancer therapies to target senescence-associated changes in the TME including for modulation of the senescent cytokine landscape.

cancer biology↗

bioRxiv2023

Sequence-based drug design using transformers

Protein-ligand interactions play central roles in biological processes and are of key importance in drug design. Deep learning-based approaches are emerging as cost-effective alternatives to high-throughput experimental methods for the screening of large libraries of ligands. Here, to predict the binding affinity between proteins and small molecules, we introduce Ligand-Transformer, a deep learning framework based on the AlphaFold2 transformer architecture. We applied Ligand-Transformer to screen inhibitors targeting the mutant EGFRLTC kinase, identifying compounds with low nanomolar potency. We then used this approach to predict the conformational population shifts induced by ABL kinase inhibitors. To show the applicability of Ligand-Transformer to disordered proteins, we explored the binding of small molecules to the Alzheimers A{beta} peptide, identifying compounds that delayed its aggregation. Overall, Ligand-Transformer illustrates the potential of transformers in accurately predicting the interactions of small molecules with both ordered and disordered proteins, thus uncovering molecular mechanisms and facilitating the initial steps in drug discovery.

bioinformatics↗

bioRxiv2023

Millimeter-scale magnetic implants paired with a fully integrated wearable device for wireless biophysical and biochemical sensing

Implantable sensors can directly interface with various organs for precise evaluation of health status. However, extracting signals from such sensors must rely on transcutaneous wires, integrated circuit chips, or cumbersome readout equipment, which increases the risks of infection, reduces the biocompatibility, or limits the portability. Here, we develop a set of millimeter-scale, chip-less and battery-less magnetic implants that can measure biophysical and biochemical signals wirelessly. In particular, the implants form two-way communications with a fully integrated wearable device, where the wearable device can induce a large-amplitude damped vibration of the magnetic implants and capture their subsequent motions in a wireless manner. Such damped vibrations reflect not only the biophysical conditions surrounding the implants movements, but also the concentration of a specific biochemical depending on the surface modification. Experiments in rat models demonstrate the capabilities in measuring cerebrospinal fluid (CSF) viscosity, intracranial pressure (ICP), and CSF glucose levels. This miniaturized system opens possibility for continuous, wireless monitoring of a wide range of biophysical and biochemical conditions within the living organism.

bioengineering↗

bioRxiv2023

Fast and accurate local ancestry inference with Recomb-Mix

The availability of large genotyped cohorts brings new opportunities for revealing the high-resolution genetic structure of admixed populations via local ancestry inference (LAI), the process of identifying the ancestry of each segment of an individual haplotype. Though current methods achieve high accuracy in standard cases, LAI is still challenging when reference populations are more similar (e.g., intra-continental), when the number of reference populations is too numerous, or when the admixture events are deep in time, all of which are increasingly unavoidable in large biobanks. Here, we present a new LAI method, Recomb-Mix. Recomb-Mix integrates the elements of existing methods of the site-based Li and Stephens model and introduces a new graph collapsing trick to simplify counting paths with the same ancestry label readout. Through comprehensive benchmarking on various simulated datasets, we show that Recomb-Mix is more accurate than existing methods in diverse sets of scenarios while being competitive in terms of resource efficiency. We expect that Recomb-Mix will be a useful method for advancing genetics studies of admixed populations.

bioinformatics↗

bioRxiv2023

Active learning for medium optimization for selective bacterial culture

Medium optimization and development for selective bacterial culture are essential for isolating and functionalizing individual bacteria in microbial communities; nevertheless, it remains challenging due to the unknown mechanisms between bacterial growth and medium components. The present study first tried combining machine learning (ML) with active learning to finetune the medium components for the selective culture of two divergent bacteria, i.e., Lactobacillus plantarum and Escherichia coli. ML models considering multiple growth parameters of the two bacterial strains were constructed to predict the finetuned medium combinations for higher specificity of bacterial growth. The growth parameters were designed as the exponential growth rate (r) and maximal growth yield (K), which were calculated according to the growth curves. The eleven chemical components in the commercially available medium MRS were subjected to medium optimization and specialization. High-throughput growth assays of both strains grown separately were performed to obtain thousands of growth curves in more than one hundred medium combinations, and the resultant datasets linking the growth parameters to the medium combinations were used for the ML training. Repeated rounds of active learning (i.e., ML model construction, medium prediction, and experimental verification) successfully improved the specific growth of a single strain out of the two. Both r and K showed maximized differentiation between the two strains. Further analysis of all data accumulated in active learning identified the decision-making medium components for growth specificity and the differentiated determinative manner of growth decision of the two strains. In summary, this study demonstrated the efficiency and practicality of active learning in medium optimization for selective culture and offered novel insights into the contribution of the chemical components to specific bacterial growth.

systems biology↗

bioRxiv2023

TranSiGen: Deep representation learning of chemical-induced transcriptional profile

With the advancement of high-throughput RNA sequencing technologies, the use of chemical-induced transcriptional profiling has greatly increased in biomedical research. However, the usefulness of transcriptomics data is limited by inherent random noise and technical artefacts that may cause systematical biases. These limitations make it challenging to identify the true signal of perturbation and extract knowledge from the data. In this study, we propose a deep generative model called Transcriptional Signatures Generator (TranSiGen), which aims to denoise and reconstruct transcriptional profiles through self-supervised representation learning.TranSiGen uses cell basal gene expression and compound molecular structure representation to infer the chemical-induced transcriptional profile. Results demonstrate the effectiveness of TranSiGen in learning and predicting differential expression genes. The representation derived from TranSiGen can also serve as an alternative phenotype information, with applications in ligand-based virtual screening, drug response prediction, and phenotype-based drug repurposing. We envisage that integrating TranSiGen into the drug discovery and mechanism research pipeline will promote the development of biomedicine.

bioinformatics↗

bioRxiv2023

Cryptography in the DNA of living cells enabled by multi-site base editing

Although DNA is increasingly being adopted as a generalizable medium for information storage and transfer, reliable methods for ensuring information security remain to be addressed. In this study, we developed and validated a cryptographic encoding scheme, Genomic Sequence Encryption (GSE), to address the challenge of information confidentiality and integrity in biological substrates. GSE enables genomic information encoding that is readable only with a cryptographic key. We show that GSE can be used for cell signatures that enable the recipient of a cell line to authenticate its origin and validate if the cell line has been modified in the interim. We implement GSE through multi-site base editing and encode information through editing across >100 genomic sites in mammalian cells. We further present an enrichment step to obtain individual stem cells with more than two dozen edits across a single genome with minimal screening. This capability can be used to introduce encrypted signatures in living animals. As an encryption scheme, GSE is falsification-proof and enables secure information transfer in biological substrates.

synthetic biology↗