Biology subjects

Zhang, G.

Publications and source records attributed to Zhang, G..

At least 271 records · Page 15Linked to original sources

bioRxiv2022

Hydrodynamic and anthropogenic disturbances co-shape microbiota rhythmicity and community assembly within intertidal groundwater-surface water continuum

Tidal hydrodynamics drive the groundwater-seawater exchange and shifts in microbiota structure in the coastal zone. However, how the coastal water microbiota structure and assembly patterns respond to periodic tidal fluctuations and anthropogenic disturbance remain unexplored in the intertidal groundwater-surface water (GW-SW) continuum, although it affects biogeochemical cycles and coastal water quality therein. Here, through hourly time-series sampling in the saltmarsh tidal creek, rhythmic patterns of microbiota structure in response to daily and monthly tidal fluctuations in intertidal surface water are disentangled for the first time. The similarity in archaeal community structures between groundwater and ebb-tide surface water (R2=0.06, p=0.2) demonstrated archaeal transport through groundwater discharge, whereas multi-source transport mechanisms led to unique bacterial biota in ebb-tide water. Homogeneous selection (58.6%-69.3%) dominated microbiota assembly in the natural intertidal GW-SW continuum and the presence of 157 rhythmic ASVs identified at ebb tide and 141 at flood tide could be attributed to different environmental selection between groundwater and seawater. For intertidal groundwater in the tidal creek affected by anthropogenically contaminated riverine inputs, higher microbial diversity and shift in community structure were primarily controlled by increased co-contribution of dispersal limitation and drift (jointly 57.8%) and enhanced microbial interactions. Overall, this study fills the knowledge gaps in the tide-driven water microbial dynamics in coastal transition zone and the response of intertidal groundwater microbiota to anthropogenic pollution of overlying waters. It also highlights the potential of microbiome analysis in enhancing coastal water quality monitoring and identifying anthropogenic pollution sources (e.g., aquaculture pathogenic Vibrio) through the detection of rhythmic microbial variances associated with intertidal groundwater discharge and seawater intrusion.

ecology↗

bioRxiv2022

Bio-friendly long-term subcellular dynamic recording by self-supervised image enhancement microscopy

Fluorescence microscopy has become an indispensable tool for revealing the dynamic regulations of cells and organelles in high resolution noninvasively. However, stochastic noise inherently restricts the upper bonds of optical interrogation quality and exacerbates the observation fidelity in encountering joint demand of high frame rate, long-term, and low photobleaching and phototoxicity. Here, we propose DeepSeMi, a self-supervised-learning-based denoising framework capable of increasing SNR by over 12 dB across various conditions. With the introduction of newly designed eccentric blind-spot convolution filters, DeepSeMi accomplished efficacious denoising requiring no clean data as references and no compromise of spatiotemporal resolution on diverse imaging systems. The computationally 15-fold multiplied photon budget in a standard confocal microscope by DeepSeMi allows for recording organelle interactions in four colors and high-frame-rate across tens of thousands of frames, monitoring migrasomes and retractosomes over a half day, and imaging ultra-phototoxicity-sensitive Dictyostelium cells over thousands of frames, all faithfully and sample-friendly. Through comprehensive validations across various cells and species over various instruments, we prove DeepSeMi is a versatile tool for reliably and bio-friendly breaking the shot-noise limit, facilitating automated analysis of massive data about cell migrations and organelle interactions.

bioengineering↗

bioRxiv2022

Targeting BET Proteins downregulates miR-33a to promote synergy with PIM inhibitors in CMML

Preclinical studies in myeloid neoplasms have demonstrated efficacy of Bromodomain and Extra-Terminal protein inhibitors (BETi). However, BETi demonstrate poor single agent activity in clinical trials. Several studies suggest that combination with other anti-cancer inhibitors may enhance the efficacy of BETi. To nominate BETi combination therapies for myeloid neoplasms, we used a chemical screen with therapies currently in clinical cancer development. We identified PIM inhibitors (PIMi) as therapeutically synergistic with BETi in myeloid leukemia models. Mechanistically, we show that PIM kinase is increased after BETi treatment, and that PIM kinase upregulation is sufficient to induce resistance to BETi and sensitize cells to PIMi. Further, we demonstrate that miR-33a downregulation is the underlying mechanism driving PIM1 upregulation. We also show that GM-CSF hypersensitivity, a hallmark of chronic myelomonocytic leukemia (CMML), represents a molecular signature for sensitivity to combination therapy and credential this using patient-derived xenografts supporting the clinical investigation of this combination.

cancer biology↗

bioRxiv2022

Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer

We analyzed large-scale post-translational modification (PTM) data to outline cell signaling pathways affected by tyrosine kinase inhibitors (TKIs) in ten lung cancer cell lines. Tyrosine phosphorylated, lysine ubiquitinated, and lysine acetylated proteins were concomitantly identified using sequential enrichment of post translational modification (SEPTM) proteomics. Machine learning was used to identify PTM clusters that represent functional modules that respond to TKIs. To model lung cancer signaling at the protein level, PTM clusters were used to create a co-cluster correlation network (CCCN) and select protein-protein interactions (PPIs) from a large network of curated PPIs to create a cluster-filtered network (CFN). Next, we constructed a Pathway Crosstalk Network (PCN) by connecting pathways from NCATS BioPlanet whose member proteins have PTMs that co-cluster. Interrogating the CCCN, CFN, and PCN individually and in combination yields insights into the response of lung cancer cells to TKIs. We highlight examples where cell signaling pathways involving EGFR and ALK exhibit crosstalk with BioPlanet pathways: Transmembrane transport of small molecules; and Glycolysis and gluconeogenesis. These data identify known and previously unappreciated connections between receptor tyrosine kinase (RTK) signal transduction and oncogenic metabolic reprogramming in lung cancer. Comparison to a CFN generated from a previous multi-PTM analysis of lung cancer cell lines reveals a common core of PPIs involving heat shock/chaperone proteins, metabolic enzymes, cytoskeletal components, and RNA-binding proteins. Elucidation of points of crosstalk among signaling pathways employing different PTMs reveals new potential drug targets and candidates for synergistic attack through combination drug therapy. Author SummaryProtein post-translational modifications (PTMs), such as phosphorylation, ubiquitination, and acetylation, are extensively employed by cell signaling pathways that regulate cell division, differentiation, migration, and cancer. We used machine learning to identify PTM clusters that represent functional modules in cell signaling pathways. These clusters were used to identify protein-protein interactions, and interactions between cell signaling pathways, that were active in lung cancer cells that were treated with anti-cancer drugs. We model these interactions as networks at three levels of granularity at the pathway, protein-protein interaction, and PTM levels. Interrogation of these networks yielded insights into molecular interactions between cell signaling pathways activated by oncogenes, transmembrane transport of small molecules, and glycolysis and gluconeogenesis. These analyses identify previously unappreciated mechanisms of crosstalk among signaling pathways between oncogenic tyrosine kinase signaling and proteins that regulate metabolic reprogramming in lung cancer, revealing new potential drug targets for combination therapy.

cancer biology↗

bioRxiv2022

Research on protein structure prediction and folding based on novel remote homologs recognition

Recognition of remote homologous structures is a necessary module in AlphaFold2 and is also essential for the exploration of protein folding pathways. Here, we developed a new method, PAthreader, which identifies remote homologous structures based on the three-track alignment of distance profiles and structure profiles originated from PDB and AlphaFold DB by deep learning. Based on the identified templates, we further enhanced state-of-the-art modelling method and explored protein folding pathways based on the residue frequency distribution of homologs and the secondary structure. The results show that the average accuracy of templates identified by PAthreader is 11.6% higher than those of HHsearch on 551 nonredundant proteins. In terms of structure modelling, PAthreader improves the performance of AlphaFold2 and ranks first in CAMEO blind test for the last three months. Furthermore, we explored protein folding pathways for 37 proteins. The results are almost consistent with biological experiments for 7 proteins, and the remaining 30 human proteins have yet to be verified by biological experiments, revealing that folding information can be exploited from remote homologous structures.

bioinformatics↗

bioRxiv2022

Genome-wide regulatory effects of STRs stabilized by elevated expression of antioxidant genes in C. elegans

Genetic variation can cause significant differences in gene expression among individuals. Although quantitative genetic mapping techniques provide ways to identify genome-wide regulatory loci, they almost entirely focus on single nucleotide variants (SNVs). Short tandem repeats (STRs) represent a large source of genetic variation with potential regulatory effects. Here, we leverage the recently generated expression and STR variation data among wild Caenorhabditis elegans strains to conduct a genome-wide analysis of how STRs affect gene expression variation. We identify thousands of expression STRs (eSTRs) showing regulatory effects and demonstrate that they explain missing heritability beyond SNV-based expression quantitative trait loci. We illustrate specific regulatory mechanisms such as how eSTRs affect splicing sites and alternative splicing efficiency. We also show that differential expression of antioxidant genes might affect STR variation systematically. Overall, we reveal the interplay between STRs and gene expression variation in a tractable model system to ultimately associate STR variation with differences in complex traits.

genetics↗

bioRxiv2022

Comprehensive structural analysis reveals broad-spectrum neutralizing antibodies against Omicron

The pandemic of COVID-19 caused by SARS-CoV-2 continues to spread around the world. Mutant strains of SARS-CoV-2 are constantly emerging. At present, Omicron variants have become mainstream. In this work, we carried out a systematic and comprehensive analysis of the reported spike protein antibodies, counting the antibodies epitopes and genotypes. We further comprehensively analyzed the impact of Omicron mutations on antibody epitopes and classified these antibodies according to their binding patterns. We found that the epitopes of one class of antibodies were significantly less affected by Omicron mutations than other classes. Binding and virus neutralization experiments show that such antibodies can effectively inhibit the immune escape of Omicron. Cryo-EM results show that this class of antibodies utilizes a conserved mechanism to neutralize SARS-CoV-2. Our results greatly help us deeply understand the impact of Omicron mutations. At the same time, it also provides guidance and insights for developing Omicron antibodies and vaccines.

microbiology↗

bioRxiv2022

A gene expression analysis and immune infiltration between lesioned and preserved subchondral bone in osteoarthritis

BackgroundOsteoarthritis (OA) is a degenerative disease which need more research. The purpose of this study was to performed gene expression analysis and immune infiltration between lesioned and preserved subchondral bone, and validation with datasets and experiment of multiple tissues. MethodsThe different expressed genes(DEGs) of GSE51588 datasets between lesioned and preserved tibial plateaus of OA patients were conducted. Moreover, functional annotation and protein-protein interaction (PPI) network were applied for exploring the potential therapeutic targets in OA subchondral bones between lesioned and preserved sides. In addition, multiple tissues were used to screen out co-expressed genes and the expression levels of identified candidate DEGs was detected by quantitative real-time polymerase chain reaction (qRT-PCR) in OA. Finally, immune infiltration analysis was conducted. ResultsA total of 1010 DEGs were identified, including upregulated 423 genes, 587 downregulated genes. Upregulated genes showed that BP terms were enriched in "skeletal system development", "sister chromatid cohesion","ossification" etc. Pathways were enriched in "Wnt signaling pathway," "Proteoglycans in cancer," Downregulated genes showed that BP terms were enriched in "inflammatory response," "xenobiotic metabolic process", "positive regulation of inflammatory response". Pathways were enriched in "Neuroactive ligand-receptor interaction", "AMPK signaling pathway" etc. JUN, TNF, IL1B,were the hub genes in the PPI network. Col1A1 and LRRC15 were screened out by multiple datasets and validated by experiments. Immune infiltration showed adipocytes and endothelial cells infiltrated less in lesioned samples. ConclusionOur research might provide valuable information for exploring the pathogenesis mechanism of OA and identifying the potential therapy targets for OA diagnosis.

molecular biology↗

bioRxiv2022

Cross-tissue multiomics studies reveal gut-brain interactions mediating the effect of Akkermansia muciniphila in counteracting fructose-induced obesity

High fructose diet is a major risk factor for metabolic syndrome (MetS). The gut bacterium Akkermansia muciniphila (A. muciniphila) has been shown to improve fructose-induced MetS, but the underlying mechanism remains unclear. Here, we investigated how A. muciniphila modulates fructose-induced MetS using multitissue, multiomics studies encompassing gut microbiota, plasma and gut metabolome, and hypothalamus single cell RNA-sequencing. A. muciniphila colonization enriched beneficial gut bacteria, increased metabolites including bile acids, endocannabinoids, and vitamins, and activated genes related to oxytocin and vasopressin signaling in hypothalamic neurons. Multiomics network analysis prioritized the metabolite oleoylethanolamide (OEA), an endocannabinoid analogue, as a potential regulator of gut-hypothalamic interaction conferred by A. muciniphila, its associated beneficial bacteria, and bile acid remodeling. Oral administration of OEA to fructose-fed mice recapitulated A. muciniphila effects, including counteracting body weight gain, enhancing thermogenesis, and ameliorating glucose intolerance. Concomitantly, OEA supplementation stimulated expression of its receptors and tight junction genes in the intestine, as well as neuronal activation marker c-Fos and oxytocin and vasopressin signaling genes in the hypothalamus. These findings underscore the regulatory role of A. muciniphila in gut microbiota homeostasis and metabolomic reprogramming, and pinpoint OEA as a key mediator of its action on the gut-hypothalamus axis in alleviating fructose-induced MetS.

systems biology↗

bioRxiv2022

Dissecting aneuploidy phenotypes by constructing Sc2.0 chromosome VII and SCRaMbLEing synthetic disomic yeast

Aneuploidy compromises genomic stability, often leading to embryo inviability, and is frequently associated with tumorigenesis and aging. Different aneuploid chromosome stoichiometries lead to distinct transcriptomic and phenotypic changes, making it helpful to study aneuploidy in tightly controlled genetic backgrounds. By deploying the engineered SCRaMbLE system to the newly synthesized Sc2.0 megabase chromosome VII (synVII), we constructed a synthetic disomic yeast and screened hundreds of SCRaMbLEd derivatives with diverse chromosomal rearrangements. Phenotypic characterization and multi-omics analysis revealed that fitness defects associated with aneuploidy could be restored by i) removing most of the chromosome content, or ii) modifying specific regions in the duplicated chromosome. These findings indicate that both chromosome copy number and chromosomal regions contribute to the aneuploidy-related phenotypes, and the synthetic yeast resource opens new paradigms in studying aneuploidy. In briefUse of SCRaMbLE and newly synthesized Mb-scale Sc2.0 chromosome VII enables insights into genotype/phenotype relationships associated with aneuploidy HighlightsO_LIDe novo design and synthesis of a Mb-scale synthetic yeast chromosome VII, carrying 11.8% sequence modifications and representing nearly 10% of the yeast genome. C_LIO_LIA disomic yeast (n + synVII) is constructed for dissecting the aneuploidy phenotype C_LIO_LISCRaMbLE enables systematic exploration of regions causing aneuploidy phenotypes C_LIO_LIChromosomal copy number and content both contribute to aneuploidy phenotypes C_LIO_LIA 20 Kb deletion on the right arm of synVII leads to fitness improvement linked to up-regulation of protein synthesis C_LI

synthetic biology↗

bioRxiv2022

Senescent cells develop PDK4-dependent hypercatabolism and form an acidic microenvironment to drive cancer resistance

Cellular senescence is a state of stable growth arrest, usually accompanied by development of the senescence-associated secretory phenotype (SASP). Although senescent cells remain metabolically active, little is known about their metabolic landscape and in vivo pathophysiological implications. Here we show that expression of the pyruvate dehydrogenase (PDH) inhibitory enzyme, pyruvate dehydrogenase kinase 4 (PDK4), is significantly upregulated in human senescent stromal cells. Preferentially expressed upon genotoxicity-induced senescence (GIS), PDK4 is negatively correlated with posttreatment survival of cancer patients. Upon cellular senescence, PDK4 shifts glucose metabolic flux from oxidative phosphorylation to aerobic glycolysis, causing enhanced lactate production and forming an acidic microenvironment. However, distinct from the cancer cell-featured Warburg effect, senescent cells maintain an intensive use of pyruvate through the tricarboxylic acid cycle (TCA), displaying increased respiration and redox activity, indicative of a special form of metabolic reprogramming. Conditioned media from PDK4+ stromal cells change global expression and promote malignancy of recipient cancer cells in vitro and accelerate tumor progression in vivo. Pharmacologically targeting PDK4 restrains the adverse effects of PDK4 in cell-based assays, while promoting tumor regression and extending posttreatment survival in preclinical trials. Together, our study substantiates the hypercatabolic nature of senescent cells, and reveals a metabolic link between senescence-associated acidic microenvironment and age-related pathologies including but not limited to cancer.

cell biology↗

bioRxiv2022

Variations in ERP Data Quality Across Paradigms, Participants, and Scoring Procedures

Although it is widely accepted that data quality for event-related potential (ERP) components varies considerably across studies and across participants within a study, ERP data quality has not received much systematic analysis. The present study used a recently developed metric of ERP data quality-- the standardized measurement error (SME)--to examine how data quality varies across different ERP paradigms, across individual participants, and across different procedures for quantifying amplitude and latency values. The EEG recordings were taken from the ERP CORE, which includes data from 40 neurotypical college students for seven widely studied ERP components: P3b, N170, mismatch negativity, N400, error-related negativity, N2pc, and lateralized readiness potential. Large differences in data quality were observed across the different ERP components, and very large differences in data quality were observed across participants. Data quality also varied depending on the algorithm used to quantify the amplitude and especially the latency of a given ERP component. These results provide an initial set of benchmark values that can be used for comparison with previous and future ERP studies. They also provide useful information for predicting effect sizes and statistical power in future studies, even with different numbers of trials. More broadly, this study provides a general approach that could be used to determine which specific experimental designs, data collection procedures, and data processing algorithms lead to the best data quality.

neuroscience↗

bioRxiv2022

Establishment Strategy and Temporal Dynamics of Tetrasphaera-Enriched Microbiome for Enhanced Biological Phosphorus Removal and Recovery

Tetrasphaera were recently identified based on the 16S rRNA gene as among the most abundant polyphosphate-accumulating organisms (PAOs) in global full-scale wastewater treatment plants (WWTPs) with enhanced biological phosphorus removal (EBPR). However, it is unclear how Tetrasphaera PAOs are selectively enriched in the context of the EBPR microbiome. In this study, an EBPR microbiome enriched with Tetrasphaera (accounting for 40% of 16S sequences on day 113) was built using a top-down design approach featuring multicarbon sources and a low dosage of allylthiourea. The microbiome showed enhanced nutrient removal (P removal ~85% and N removal ~80%) and increased P recovery (up to 23.2 times) compared with the seeding activated sludge from a local full-scale WWTP. The supply of 1 mg/L allylthiourea promoted the coselection of Tetrasphaera PAOs and Microlunatus PAOs and sharply reduced the relative abundance of both ammonia oxidizer Nitrosomonas and putative competitors Brevundimonas and Paracoccus, facilitating the establishment of the EBPR microbiome. Based on 16S rRNA gene analysis, a putative novel PAO species, EBPR-ASV0001, was identified with Tetrasphaera japonica as its closest relative. This study provides new knowledge on the establishment of a Tetrasphaera-enriched microbiome facilitated by allylthiourea, which can be further exploited to guide future process upgrading and optimization to achieve and/or enhance simultaneous biological phosphorus and nitrogen removal from high-concentration wastewater.

bioengineering↗

bioRxiv2022

Dicamba drift alters patterns of chewing herbivory in three common agricultural weeds

How agricultural regimes, such as novel herbicide exposure, may influence plant-herbivore interactions and specifically patterns of plant herbivory has come under increased interest in recent years due to rapidly changing herbicide use in agroecosystems. This paper examines patterns of plant herbivory using three common agricultural weeds exposed to low doses of dicamba, a synthetic auxin herbicide that is exponentially increasing in use given the adoption of dicamba tolerant crops. We used a replicated field study to examine how the amount and type of chewing herbivory may be altered in Ipomoea purpurea (common morning glory, Convolvulaceae), Datura stramonium (jimsonweed, Solanaceae), and Abutilon theophrasti (velvetleaf, Malvaceae) exposed to dicamba drift (i.e., 1% of the field dose). We found an increase in chewing herbivory damage when plants were exposed to dicamba and changes in the type of herbivory following exposure. Chewing herbivory differed among species in the presence of dicamba drift: A. theophrasti and D. stramonium showed more total leaf-chewing herbivory than controls, but I. purpurea showed no difference in the overall amount of herbivory. We also found that the type of herbivory was significantly altered in drift. A. theophrasti and I. purpurea both exhibited declines in hole feeding but increases in margin feeding, whereas D. stramonium showed no such changes. Overall, our results show that herbicide drift can induce shifts in plant-herbivore interactions, highlighting the need for mechanistic studies to uncover the cause underlying the shifts and comparative studies on weed communities to understand long-term consequences.

plant biology↗

bioRxiv2022

Species-specific traits mediate avian demographic responses under past climate change

Anticipating species responses to environmental change is a pressing mission in biodiversity conservation. Despite decades of research investigating how climate change may affect population sizes, historical context is lacking and the traits which mediate demographic sensitivity to changing climate remain elusive. We use whole-genome sequence data to reconstruct the demographic histories of 263 bird species over the past million years and identify networks of interacting morphological and life-history traits associated with changes in effective population size (Ne) in response to climate warming and cooling. Our results identify direct and indirect effects of key traits representing dispersal, reproduction, and survival on long-term demographic responses to climate change, thereby highlighting traits most likely to influence population responses to on-going climate warming. One-Sentence SummaryInteracting traits influence sensitivity of bird population sizes to climate warming and cooling over the past million years.

evolutionary biology↗

bioRxiv2022

Improved model quality assessment using sequence and structural information by enhanced deep neural networks

Protein model quality assessment plays an important role in protein structure prediction, protein design, and drug discovery. In this work, DeepUMQA2, a substantially improved version of DeepUMQA for protein model quality assessment, is proposed. First, sequence features containing protein co-evolution information and structural features reflecting family information are extracted to complement model-dependent features. Second, a novel backbone network based on triangular multiplication update and axial attention mechanism is designed to enhance information exchange between inter-residue pairs. On CASP13 and CASP14 datasets, the performance of DeepUMQA2 increases by 20.5% and 20.4% compared with DeepUMQA, respectively (measured by top 1 loss). Moreover, on the three-month CAMEO dataset (March 11 to June 04, 2022), DeepUMQA2 outperforms DeepUMQA by 15.5% (measured by local AUC0,0.2) and ranks first among all competing server methods in CAMEO blind test. Experimental results show that DeepUMQA2 outperforms state-of-the-art model quality assessment methods, such as ProQ3D-LDDT, ModFOLD8, DeepAccNet, Atom_ProteinQA, and QMEAN3.

bioinformatics↗

bioRxiv2022

Stability of SARS-CoV-2 in cold-chain transportation environments and the efficacy of disinfection measures

Cold-chain environment could extend the survival duration of SARS-CoV-2 and increases the risk of transmission. However, the effect of clod-chain environmental factors and packaging materials on SARS-CoV-2 stability and the efficacy of intervention measures to inactivate SARS-CoV-2 under cold-chain environment remains uncertain. This study aimed to unravel cold-chain environmental factors that preserved the stability of SARS-CoV-2 and disinfection measures against SARS-CoV-2 under the cold-chain environment. The spike gene of SARS-CoV-2 isolated from Wuhan hu-1 was used to construct the SARS-CoV-2 pseudovirus and used as model of the SARS-CoV-2 virus. The decay rate of SARS-CoV-2 pseudovirus in the cold-chain environment, various types of packaging material surfaces i.e., PE plastic, stainless steel, Teflon and cardboard, and in frozen seawater was investigated. The influence of LED visible light(wavelength 450 nm-780 nm) and airflow movement on the stability of SARS-CoV-2 pseudovirus at -18{degrees} C were subsequently assessed. The results show that SARS-CoV-2 pseudovirus decayed more rapidly on porous cardboard surface compared with the non-porous surfaces including PE plastic, stainless steel and Teflon. Compared with 25{degrees} C, the decay rate of SARS-CoV-2 pseudovirus was significantly lower at low temperature. Seawater preserved viral stability both at -18{degrees} C and repeated freeze-thawing cycles compared with deionized water. LED visible light illumination and airflow movement environment at -18{degrees} C reduced the SARS-CoV-2 pseudovirus stability. In conclusion, our results indicate cold-chain temperature and seawater as risk factors for SARS-CoV-2 transmission and LED visible light illumination and airflow movement as possible disinfection measures of SARS-CoV-2 under the cold-chain environment. ImportanceIt is widely recognized that low temperature is a condition for maintaining virus vitality, and cold-chain transportation spreads the events of the SARS-CoV-2 were reported. This study provides that the decay rate of the SARS-CoV-2 pseudovirus at low temperatures varies on different packaging materials, and salt ions present in frozen foods such as seafood may protect virus survival. These results provide evidence for the possibility of SARS-CoV-2 transmission through cold-chain transport and also suggest the importance for disinfection of items. However, the commonly used disinfection methods of ultraviolet radiation and chemical reagents are generally not suitable for the disinfection of frozen food. Our study shows LED visible light illumination and airflow movement as possible disinfection measures of SARS-CoV-2 under the cold-chain environment. This has implications for reducing the long-distance transmission of the virus through cold-chain transportation.

microbiology↗

bioRxiv2022

Propagation dynamics of electrotactic motility in large epithelial cell sheets

Directional migration initiated at the wound edge leads epithelial sheets to migrate in wound healing. How such coherent migration is achieved is not well understood. Here we used electric fields to induce robust migration of sheets of human keratinocytes and developed an in silico model to characterize initiation and propagation of epithelial collective migration. Electric fields initiate increase in migrations directionality and speed at the leading edge. The increases propagate across the epithelial sheets, resulting in directional migration of cell sheets as coherent units. Both the experimental and in silico models demonstrated vector-like integration of the electric and default directional cues at the free edge in space and time. The resultant collective migration is remarkably consistent in experiments and modeling, both qualitatively and quantitatively. The keratinocyte model thus faithfully reflects key features of epithelial migration as a coherent tissue in vivo, e.g. that leading cells lead, and that epithelium maintains cell- cell junction.

cell biology↗