Biology subjects

Tan, C.

Publications and source records attributed to Tan, C..

At least 73 records · Page 4Linked to original sources

bioRxiv2022

Vascular endothelial growth factor A contributes to the increasing of mammalian respiratory epithelial permeability induced by Pasteurella multocida infection

Infections with Pasteurella multocida can cause significant zoonotic respiratory problems in both humans and animals. In vivo tests in mouse infection models were used to investigate the mechanisms of respiratory epithelial barrier dysfunction during respiratory bacterial infection with these pathogens. Results revealed that P. multocida infection significantly increased epithelial permeability and increased expression of vascular endothelial growth factor A (VEGFA) and endothelial nitric oxide synthase (eNOS) in murine tracheae and lungs. In murine lung epithelial cell (MLE-12) models, P. multocida infection decreased the expression of tight junctions (ZO-1) and adherens junctions ({beta}-catenin, E-cadherin), but induced the activation of the hypoxia-inducible factor-1 (HIF-1) and VEGFA signaling. When expression of HIF-1 is suppressed, the induction of VEGFA and ZO-1expression by P. multocida infection is decreased. We also found that intervention of HIF-1 and VEGFA signaling affected infection outcomes caused by respiratory bacteria in mouse models. Most importantly, we demonstrated that P. multocida infection increased permeability of human respiratory epithelial cells and this process was associated with the activation of the HIF-1 and VEGFA signaling and likely contributes to the pathogenesis of P. multocida in humans. ImportanceMammalian respiratory epithelium forms the first line of defense against infections with Pasteurella multocida, an important zoonotic respiratory pathogen. In this study, we found P. multocida infection increased respiratory epithelial permeability and promoted the induction of the hypoxia-HIF-1-VEGFA axis in both mouse and murine cell models. Similar findings were also demonstrated in human respiratory epithelial cells. The results from this study gain important knowledge about the pathogenesis of P. multocida causing infections in both animals and humans.

microbiology↗

bioRxiv2022

Structure-Preserving and Batch-Correcting Visualization Using Deep Manifold Transformation for Single-cell RNA-Seq Profiles

Dimensionality reduction and visualization play an important role in biological data analysis, such as data interpretation of single-cell RNA sequence (scRNA-seq). It is desired to have a visualization method that can not only be applicable to various application scenarios, including cell clustering and trajectory inference, but also satisfy a variety of technical requirements, especially the ability to preserve inherent structure of data and handle with batch effects. However, no existing methods can accommodate these requirements in a unified framework. In this paper, we propose a general visualization method, deep visualization (DV), that possesses the ability to preserve inherent structure of data and handle batch effects and is applicable to a variety of datasets from different application domains and dataset scales. The method embeds a given dataset into a 2- or 3-dimensional visualization space, with either a Euclidean or hyperbolic metric depending on a specified task type with type static (at a time point) or dynamic (at a sequence of time points) scRNA-seq data, respectively. Specifically, DV learns a structure graph to describe the relationships between data samples, transforms the data into visualization space while preserving the geometric structure of the data and correcting batch effects in an end-to-end manner. The experimental results on nine datasets in complex tissue from human patients or animal development demonstrate the competitiveness of DV in discovering complex cellular relations, uncovering temporal trajectories, and addressing complex batch factors. We also provide a preliminary attempt to pre-train a DV model for visualization of new incoming data.

bioinformatics↗

bioRxiv2022

The complex roles of genomic DNA modifications of bacteriophage T4 in resistance to nuclease-based defense systems of E. coli

The interplay between defense and counter-defense systems of bacteria and phages is a major driver of evolution of both organisms, leading to their greatest genetic diversity. Bacterial restriction-modification (R-M) and CRISPR-Cas are two well-known defense systems that target phage DNAs through their nuclease activities, whereas phages have developed counter-defense systems through covalent modifications of their genomes. Recent studies have revealed many novel nuclease-containing antiphage systems, which leads to the question of whats the role of phage genome modifications in countering these systems. Here, we scanned Escherichia coli genome sequences available in the NCBI databases and found abundant nuclease-containing defense systems, indicating that phage genomic DNA could be a major target for E. coli to restrict infection. From a collection of 816 E. coli strains, we cloned and validated 14 systems. Particularly, Gabija and type III Druantia systems have broad antiphage activities. Using wild-type phage T4 and its mutants, T4 (hmC) and T4 (C), which contain glucosyl-5-hydroxymethylcytosines, 5-hydroxymethylcytosines, and unmodified cytosines in the genomic DNA respectively, we revealed the complex roles of genomic modification of phage T4 in countering the nuclease-containing defense systems other than simply blocking the degradation of genomic DNA by nuclease.

microbiology↗

bioRxiv2022

The Nucleocapsid Protein Of SARS-CoV-2, Combined With ODN-39M, Is A Potential Component For An Intranasal Bivalent Pancorona Vaccine

Despite the rapid development of vaccines and their reported efficacy for controlling the COVID-19 waves, two key challenges remain: the scope of the immunity against upcoming variants and zoonosis events, and the induction of mucosal immunity able to clear the virus in the upper respiratory tract for halting the transmission. The present study is aiming at assessing a potential component for a new generation of vaccines so as to overcome such limitations. The recombinant nucleocapsid (N) protein from SARS-CoV-2 Delta variant was combined with a phosphodiester backbone CpG ODN (ODN-39M), forming high molecular weight aggregates. The evaluation of its immunogenicity in Balb/C mice revealed that only administration by intranasal route induced a systemic cross-reactive Cell-Mediated-Immunity (CMI). In turn, this combination was able to induce anti-N IgA in lungs, which along with the specific IgG in sera and CMI in spleen, resulted cross-reactive against the nucleocapsid protein of SARS-CoV-1. Furthermore, the nasal administration of the N+ODN-39M preparation combined with the RBD Delta protein, as inductor of neutralizing Abs, enhanced the local and systemic immune response against RBD with a modulation toward a Th1 pattern. Taken together, these results make the N+ODN-39M preparation a suitable component for a future intranasal pancorona vaccine against Sarbecoviruses. Particularly, the bivalent vaccine formulation N+ODN-39M+RBD could be used as an effective nasal booster in previously vaccinated population.

immunology↗

bioRxiv2022

Nucleotide resolution genetic mapping in pigs by publicly accessible whole genome imputation

Genetic mapping to identify genes and alleles associated with or causing economically important quantitative trait variation in livestock animals such as pigs is a major goal in the genetic improvement animals. Despite recent advances in high throughput genotyping technologies, resolution of genetic mapping in pigs remains poor due in part to the low density of genotyped variant sites. In this study, we overcame this limitation by developing a reference haplotype panel for pigs based on 2,259 whole genome sequenced animals representing 44 pig breeds. We optimized the imputation procedure to achieve an average concordance rate in excess of 97%, non-reference concordance rate 91%, and r2 0.89. We demonstrated that genotype imputation using this resource can dramatically improve resolution of genetic mapping. Finally, we developed a public web server (swimgeno.org) to allow the pig genetics community to fully utilize this resource. We expect the resource and server to significantly facilitate genetic mapping and accelerate genetic improvement in pigs.

genomics↗

bioRxiv2022

Improving the RNA velocity approach using long-read single cell sequencing

The concept of RNA velocity has been recently developed that allowed to look at the otherwise static single-cell RNA sequencing data in a dynamic way, which permitted inferences about cell fates. However, the more precise parameters, such as the number of exons/introns, can also be determined using long-read methods. Comparing the numbers of exons and introns allows including more genes for downstream velocity analysis and resolves the precise cell fate. The recently developed concept of "RNA velocity" concerns with dynamic changes in mRNA expression and complements single-cell RNA sequencing (scRNA-seq) data, which are static snapshots of a certain cell state taken at a given time point1. RNA velocity measures the change in mRNA abundance by differentiating the newly transcribed unspliced pre-mRNAs from mature spliced mRNAs. The rapidly developing long-read sequencing technology lends itself for RNA velocity analysis of scRNA-seq data, which was previously performed primarily using second-generation sequencing.

bioinformatics↗

bioRxiv2022

Lung spatial profiling reveals a T cell signature in COPD patients with fatal SARS-CoV-2 infection

RationalePeople with pre-existing lung diseases like chronic obstructive pulmonary disease (COPD) are more likely to get very sick from SARS-CoV-2 disease 2019 (COVID-19), but an interrogation of the immune response to COVID-19 infection, spatial throughout the lung structure is lacking in patients with COPD. ObjectivesTo profile the immune microenvironment of lung parenchyma, airways, and vessels of never- and ever-smokers with or without COPD, whom all died of COVID-19, using spatial transcriptomic and proteomic profiling. FindingsThe parenchyma, airways, and vessels of COPD patients, compared to control lungs had: 1) significant enrichment for lung resident CD45RO+ memory T cells; 2) downregulation of genes associated with T cell antigen-priming and memory T cell differentiation; 3) higher expression of proteins associated with SARS-CoV-2 entry and major receptor ubiquitously across the ROIs and in particular the lung parenchyma, despite similar SARS-CoV-2 structural gene expression levels. ConclusionsThe lung parenchyma, airways, and vessels of COPD patients have increased T-lymphocytes with a blunted memory T cell response and a more invasive SARS-CoV-2 infection pattern, and may underlie the higher death toll observed with COVID-19.

immunology↗

bioRxiv2022

Munc13 supports vesicle fusogenicity after disrupting active zone scaffolds and synaptic vesicle docking

Active zones consist of protein scaffolds that are tightly attached to the presynaptic plasma membrane. They dock and prime synaptic vesicles, couple them to Ca2+ entry, and target neurotransmitter release to postsynaptic receptor domains. Simultaneous RIM+ELKS ablation disrupts these scaffolds, abolishes vesicle docking and removes active zone-targeted Munc13, but some vesicles remain releasable. This enduring vesicular fusogenicity may be Munc13-independent or be mediated by non-active zone-anchored Munc13. We tested its Munc13-dependence by ablating Munc13-1 and Munc13-2 on top of RIM+ELKS in cultured hippocampal neurons. The hextuple knockout synapses lacked docked vesicles, but other ultrastructural features were near-normal despite the strong genetic manipulation. Removing Munc13 in addition to RIM+ELKS further impaired action potential-evoked release by decreasing the remaining pool of releasable vesicles. We conclude that Munc13 can support some fusogenicity without RIM and ELKS, and that presynaptic recruitment of Munc13, even without active zone-anchoring, suffices to generate some fusion-competent vesicles.

neuroscience↗

bioRxiv2022

Inflammaging in human photoexposed skin: Early onset of senescence and imbalanced epidermal homeostasis across the decades.

Inflammaging is a theory of aging which purports that low-level chronic inflammation leads to cellular dysfunction and premature aging of surrounding tissue. Skin is susceptible to inflammaging because it is the first line of defense from the environment, particularly solar radiation. To better understand the impact of aging and photoexposure on epidermal biology we performed a systems biology-based analysis of photoexposed face and arm and photoprotected buttock sites from women between the ages of 20s to 70s. Biopsies were analyzed by histology, transcriptomics, and proteomics and skin surface biomarkers collected from tape strips. We identified morphological changes with age of epidermal thinning, rete ridge pathlength loss, and stratum corneum thickening. The SASP biomarkers IL-8 and IL-1RA/IL1- were consistently elevated in face across age and cis/trans-urocanic acid were elevated in arms and face with age. In older arms, the DNA damage response biomarker 53BP1 showed higher puncti numbers in basal layers and epigenetic aging was accelerated. Genes associated with differentiation and senescence show increasing expression in the 30s whereas genes associated with hypoxia and glycolysis increase in the 50s. Proteomics comparing 60s vs 20s confirmed elevated levels of differentiation and glycolytic related proteins. Representative immunostaining for proteins of differentiation, senescence, and oxygen sensing/hypoxia shows similar relationships. This systems biology-based analysis provides a body of evidence that young photoexposed skin is undergoing inflammaging. We propose the presence of chronic inflammation in young skin contributes to an imbalance of epidermal homeostasis that leads to a prematurely aged appearance during later life.

systems biology↗

bioRxiv2022

Endothelial FOXC1 and FOXC2 promote intestinal regeneration after ischemia-reperfusion injury

Intestinal ischemia induces mucosal damage while simultaneously activating intestinal stem cells (ISCs), which subsequently regenerate the damaged intestinal epithelium. However, whether paracrine factors secreted from vascular endothelial cells (ECs) - blood and lymphatic ECs (BECs and LECs, respectively) - regulate ISC-mediated regeneration have yet to be elucidated. Here, we identify FOXC1 and FOXC2 as essential regulators of paracrine signaling in regeneration of the small intestine after ischemia-reperfusion (I/R) injury. EC- and LEC-specific deletions of Foxc1, Foxc2, or both in mice augment I/R-induced intestinal damage by causing defects in vascular regrowth, expression of the chemokine CXCL12 and the Wnt activator R- spondin 3 in BECs and LECs, respectively, and activation of Wnt signaling in ISCs. Treatment with CXCL12 and R-spondin 3 rescues the I/R-induced intestinal damage in EC- and LEC-Foxc mutant mice, respectively. This study provides evidence that FOXC1 and FOXC2 are required for intestinal regeneration by stimulating paracrine CXCL12 and Wnt signaling.

molecular biology↗

bioRxiv2022

Frequency dependent growth of bacteria in living materials

The fusion of living bacteria and man-made materials represents a new frontier in medical and biosynthetic technology. However, the principles of bacterial signal processing inside three dimensional and fluctuating environments of synthetic materials remain elusive. Here, we study bacterial growth in a three-dimensional hydrogel. We find that bacteria expressing an antibiotic resistance module can take advantage of ambient kinetic disturbances to improve growth while encapsulated. We show that these changes in bacterial growth are specific to disturbance frequency and hydrogel density. This remarkable specificity is consistent with stochastic resonance theory, which we leverage to explain how bacteria can integrate spatial and temporal information to control growth. This research provides a quantitative foundation for the control of living materials and a systematic framework towards understanding bacterial information processing in three-dimensional environments.

biophysics↗

bioRxiv2022

Towards Effective and Generalizable Fine-tuning for Pre-trained Molecular Graph Models

Graph Neural Networks (GNNs) and Transformer have emerged as dominant tools for AI-driven drug discovery. Many state-of-the-art methods first pre-train GNNs or the hybrid of GNNs and Transformer on a large molecular database and then fine-tune on downstream tasks. However, different from other domains such as computer vision (CV) or natural language processing (NLP), getting labels for molecular data of downstream tasks often requires resource-intensive wet-lab experiments. Besides, the pre-trained models are often of extremely high complexity with huge parameters. These often cause the fine-tuned model to over-fit the training data of downstream tasks and significantly deteriorate the performance. To alleviate these critical yet under-explored issues, we propose two straightforward yet effective strategies to attain better generalization performance: 1. MolAug, which enriches the molecular datasets of down-stream tasks with chemical homologies and enantiomers; 2. WordReg, which controls the complexity of the pre-trained models with a smoothness-inducing regularization built on dropout. Extensive experiments demonstrate that our proposed strategies achieve notable and consistent improvements over vanilla fine-tuning and yield multiple state-of-the-art results. Also, these strategies are model-agnostic and readily pluggable into fine-tuning of various pre-trained molecular graph models. We will release the code and the fine-tuned models.

bioinformatics↗

bioRxiv2022

Genetic Impairment of Succinate Metabolism Disrupts Bioenergetic Sensing in Adrenal Neuroendocrine Tumor

Metabolic dysfunction mutations can impair energy sensing and cause cancer. Loss of function of mitochondrial TCA cycle enzyme, succinate dehydrogenase B (SDHB) results in various forms of cancer typified by pheochromocytoma (PC). Here we delineate a signaling cascade where the loss of SDHB induces the Warburg effect in PC tumors, triggers dysregulation of Ca2+ homeostasis, and aberrantly activates calpain and the protein kinase Cdk5, through conversion of its cofactor from p35 to p25. Consequently, aberrant Cdk5 initiates a cascade of phospho- signaling where GSK3 inhibition inactivates energy sensing by AMP-kinase through dephosphorylation of the AMP-kinase {gamma} subunit, PRKAG2. Overexpression of p25-GFP in mouse adrenal chromaffin cells also elicits this phosphorylation signaling and causes PC tumor formation. A novel Cdk5 inhibitor, MRT3-007, reversed this phospho-cascade, invoking an anti- Warburg effect, cell cycle arrest, and senescence-like phenotype. This therapeutic approach halted tumor progression in vivo. Thus, we reveal an important novel mechanistic feature of metabolic sensing and demonstrate that its dysregulation underlies tumor progression in PC and likely other cancers. HighlightsO_LILoss of SDHB function in pheochromocytoma causes Ca2+ dysregulation, calpain activation, and aberrant activation of the protein kinase Cdk5. C_LIO_LIHyperactive Cdk5 deregulates a GSK3/PRKAG2/AMPK signaling cascade. C_LIO_LIp25 overexpression and consequent aberrant Cdk5 activity in chromaffin cells causes pheochromocytoma. C_LIO_LIInhibition of Cdk5 activates the PRKAG2/AMPK/p53 signaling to rescue cell senescence and block PC tumor progression. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=175 SRC="FIGDIR/small/475410v2_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@16f0a48org.highwire.dtl.DTLVardef@10c1c7aorg.highwire.dtl.DTLVardef@21b100org.highwire.dtl.DTLVardef@1eb8674_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2021

The Long Noncoding RNA FEDORA is a Cell-Type- and Sex-Specific Regulator of Depression

Women suffer from depression at twice the rate of men, but the underlying molecular mechanisms are poorly understood. Here, we identify dramatic baseline sex differences in expression of long noncoding RNAs (lncRNAs) in human postmortem brain tissue that are profoundly lost in depression. One such lncRNA, RP11-298D21.1 (which we termed FEDORA), is enriched in oligodendrocytes and neurons and upregulated in several cortical regions of depressed females but not males. We found that virally-expressing FEDORA selectively either in neurons or in oligodendrocytes of prefrontal cortex promoted depression-like behavioral abnormalities in female mice only, changes associated with cell-type-specific regulation of synaptic properties, myelin thickness, and gene expression. We also found that blood FEDORA levels have diagnostic significance for depressed women. These findings demonstrate the important role played by lncRNAs, and FEDORA in particular, in shaping the sex-specific landscape of the brain and contributing to sex differences in depression.

neuroscience↗

bioRxiv2021

Reconstructing essential active zone functions within a synapse

Active zones are molecular machines that control neurotransmitter release through synaptic vesicle docking and priming, and through coupling of these vesicles to Ca2+ entry. The complexity of active zone machinery has made it challenging to determine which mechanisms drive these roles in release. Here, we induce RIM+ELKS knockout to eliminate active zone scaffolding networks, and then reconstruct each active zone function. Re-expression of RIM1-Zn fingers positioned Munc13 on undocked vesicles and rendered them release-competent. Reconstitution of release-triggering required docking of these vesicles to Ca2+ channels. Fusing RIM1-Zn to CaV{beta}4-subunits sufficed to restore docking, priming and release-triggering without reinstating active zone scaffolds. Hence, exocytotic activities of the 80 kDa CaV{beta}4-Zn fusion protein bypassed the need for megadalton-sized secretory machines. These data define key mechanisms of active zone function, establish that fusion competence and docking are mechanistically separable, and reveal that active zone scaffolding networks are not required for release.

neuroscience↗

bioRxiv2021

Large cells activate global protein degradation to maintain cell size homeostasis

Proliferating animal cells maintain a stable size distribution over generations despite fluctuations in cell growth and division size. This tight control of cell size involves both cell size checkpoints, which delay cell cycle progression in small cells, and size-dependent regulation of mass accumulation rates. While we previously identified the p38 MAPK pathway as a key regulator of the mammalian cell size checkpoint, the mechanism of size-dependent growth rate regulation has remained elusive. Here, we quantified global rates of protein synthesis and degradation in cells of varying sizes, both under unperturbed conditions and in response to perturbations that trigger size-dependent compensatory growth slowdown. We found that protein synthesis rates scale proportionally with cell size across cell cycle stages and experimental conditions. In contrast, oversized cells that undergo compensatory growth slowdown exhibit a superlinear increase in proteasome-mediated protein degradation, with accelerated protein turnover per unit mass, suggesting activation of the proteasomal degradation pathway. Both nascent and long-lived proteins contribute to the elevated protein degradation during compensatory growth slowdown, with long-lived proteins playing a crucial role at the G1/S transition. Notably, large G1/S cells exhibit particularly high efficiency in protein degradation, surpassing that of similarly sized or larger cells in S and G2, coinciding with the timing of the most stringent size control in animal cells. These results collectively suggest that oversized cells reduce their growth efficiency by activating global proteasome-mediated protein degradation to promote cell size homeostasis.

cell biology↗

bioRxiv2021

Implementation of residue-level coarse-grained models in GENESIS for large-scale molecular dynamics simulations

Residue-level coarse-grained (CG) models have become one of the most popular tools in biomolecular simulations in the trade-off between modeling accuracy and computational efficiency. To investigate large-scale biological phenomena in molecular dynamics (MD) simulations with CG models, unified treatments of proteins and nucleic acids, as well as efficient parallel computations, are indispensable. In the GENESIS MD software, we implement several residue-level CG models, covering structure-based and context-based potentials for both well-folded biomolecules and intrinsically disordered regions. An amino acid residue in protein is represented as a single CG particle centered at the C atom position, while a nucleotide in RNA or DNA is modeled with three beads. Then, a single CG particle represents around ten heavy atoms in both proteins and nucleic acids. The input data in CG MD simulations are treated as GROMACS-style input files generated from a newly developed toolbox, GENESIS-CG-tool. To optimize the performance in CG MD simulations, we utilize multiple neighbor lists, each of which is attached to a different nonbonded interaction potential in the cell-linked list method. We found that random number generations for Gaussian distributions in the Langevin thermostat are one of the bottlenecks in CG MD simulations. Therefore, we parallelize the computations with message-passing-interface (MPI) to improve the performance on PC clusters or supercomputers. We simulate Herpes simplex virus (HSV) type 2 B-capsid and chromatin models containing more than 1,000 nucleosomes in GENESIS as examples of large-scale biomolecular simulations with residue-level CG models. This framework extends accessible spatial and temporal scales by multi-scale simulations to study biologically relevant phenomena, such as genome-scale chromatin folding or phase-separated membrane-less condensations. Author summaryMolecular dynamics (MD) simulations have been widely used to investigate biological phenomena that are difficult to study only with experiments. Since all-atom MD simulations of large biomolecular complexes are computationally expensive, coarse-grained (CG) models based on different approximations and interaction potentials have been developed so far. There are two practical issues in biological MD simulations with CG models. The first issue is the input file generations of highly heterogeneous systems. In contrast to well-established all-atom models, specific features are introduced in each CG model, making it difficult to generate input data for the systems containing different types of biomolecules. The second issue is how to improve the computational performance in CG MD simulations of heterogeneous biological systems. Here, we introduce a user-friendly toolbox to generate input files of residue-level CG models containing folded and disordered proteins, RNAs, and DNAs using a unified format and optimize the performance of CG MD simulations via efficient parallelization in GENESIS software. Our implementation will serve as a framework to develop novel CG models and investigate various biological phenomena in the cell.

biophysics↗

bioRxiv2021

Direct carbon capture for production of high-performance biodegradable plastic by cyanobacterial cell factory

Plastic pollution has become one of the most pressing environmental issues today, leading to an urgent need to develop biodegradable plastics1-3. Polylactic acid (PLA) is one of the most promising biodegradable materials because of its potential applications in disposable packaging, agriculture, medicine, and printing filaments for 3D printers4-6. However, current biosynthesis of PLA entirely uses edible biomass as feedstock, which leads to competition for resources between material production and food supply7,8. Meanwhile, excessive emission of CO2 that is the most abundant carbon source aggravates global warming, and climate instability. Herein, we first developed a cyanobacterial cell factory for the de novo biosynthesis of PLA directly from CO2, using a combinational strategy of metabolic engineering and high-density cultivation (HDC). Firstly, the heterologous pathway for PLA production, which involves engineered D-lactic dehydrogenase (LDH), propionate CoA-transferase (PCT), and polyhydroxyalkanoate (PHA) synthase, was introduced into Synechococcus elongatus PCC7942. Subsequently, different metabolic engineering strategies, including pathway debottlenecking, acetyl-CoA self-circulation, and carbon-flux redirection, were systematically applied, resulting in approximately 19-fold increase to 15 mg/g dry cell weight (DCW) PLA compared to the control. In addition, HDC increased cell density by 10-fold. Finally, the PLA titer of 108 mg/L (corresponding to 23 mg/g DCW) was obtained, approximately 270 times higher than that obtained from the initially constructed strain. Moreover, molecular weight (Mw, 62.5 kDa; Mn, 32.8 kDa) of PLA produced by this strategy was among the highest reported levels. This study sheds a bright light on the prospects of plastic production from CO2 using cyanobacterial cell factories.

bioengineering↗