Biology subjects

Li, S.

Publications and source records attributed to Li, S..

At least 1,063 records · Page 59Linked to original sources

bioRxiv2020

Paradoxical effects of cigarette smoke and COPD on SARS-CoV2 infection and disease

IntroductionHow cigarette smoke (CS) and chronic obstructive pulmonary disease (COPD) affect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and severity is controversial. We investigated the protein and mRNA expression of SARS-CoV-2 entry receptor ACE2 and proteinase TMPRSS2 in lungs from COPD patients and controls, and lung tissue from mice exposed acutely and chronically to CS. Also, we investigated the effects of CS exposure on SARS-CoV-2 infection in human bronchial epithelial cells. MethodsIn Cohort 1, ACE2-positive cells were quantified by immunostaining in FFPE sections from both central and peripheral airways. In Cohort 2, we quantified pulmonary ACE2 protein levels by immunostaining and ELISA, and both ACE2 and TMPRSS2 mRNA levels by RT-qPCR. In C57BL/6 WT mice exposed to air or CS for up to 6 months, pulmonary ACE2 protein levels were quantified by triple immunofluorescence staining and ELISA. The effects of CS exposure on SARS-CoV-2 infection were evaluated after 72hr in vitro infection of Calu-3 cells. After SARS-CoV-2 infection, the cells were fixed for IF staining with dsRNA-specific J2 monoclonal Ab, and cell lysates were harvested for WB of viral nucleocapsid (N) protein. Supernatants (SN) and cytoplasmic lysates were obtained to measure ACE2 levels by ELISA. ResultsIn both human cohorts, ACE2 protein and mRNA levels were decreased in peripheral airways from COPD patients versus both smoker and NS controls, but similar in central airways. TMPRSS2 levels were similar across groups. Mice exposed to CS had decreased ACE2 protein levels in their bronchial and alveolar epithelia versus air-exposed mice exposed to 3 and 6 months of CS. In Calu3 cells in vitro, CS-treatment abrogated infection to levels below the limit of detection. Similar results were seen with WB for viral N protein, showing peak viral protein synthesis at 72hr. ConclusionsACE2 levels were decreased in both bronchial and alveolar epithelial cells from uninfected COPD patients versus controls, and from CS-exposed versus air-exposed mice. CS-pre-treatment did not affect ACE2 levels but potently inhibited SARS-CoV-2 replication in this in vitro model. These findings urge to further investigate the controversial effects of CS and COPD on SARS-CoV2 infection.

immunology↗

bioRxiv2020

LinearTurboFold: Linear-Time RNA Structural Alignment and Conserved Structure Prediction with Applications to Coronaviruses

The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in SARS-CoV-2 genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and align multiple RNA homologs, scale at best cubically with sequence length, and are thus infeasible for coronaviruses, which possess the longest genomes ([~]30,000 nt) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single sequence folding as well as local folding methods with short window sizes, which inevitably neglect long-range interactions that are crucial in RNA functions. Here we present LinearTurboFold, an efficient algorithm for folding RNA homologs that scales linearly with sequence length, enabling unprecedented global structural analysis on SARS-CoV-2. Surprisingly, on a group of SARS-CoV-2 and SARS-related genomes, LinearTurbo-Folds purely in silico prediction not only is close to experimentally-guided models for local structures, but also goes far beyond them by capturing the end-to-end pairs between 5 and 3 UTRs ([~]29,800 nt apart) that match perfectly with a purely experimental work. Furthermore, LinearTurboFold identifies novel conserved structures and conserved accessible regions as potential targets for designing efficient and mutation-insensitive small-molecule drugs, antisense oligonucleotides, siRNAs, CRISPR-Cas13 guide RNAs and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and full-length genome studies, and will be a useful tool in fighting the current and future pandemics. Significance StatementConserved RNA structures are critical for designing diagnostic and therapeutic tools for many diseases including COVID-19. However, existing algorithms are much too slow to model the global structures of full-length RNA viral genomes. We present LinearTurboFold, a linear-time algorithm that is orders of magnitude faster, making it the first method to simultaneously fold and align whole genomes of SARS-CoV-2 variants, the longest known RNA virus ([~]30 kilobases). Our work enables unprecedented global structural analysis and captures long-range interactions that are out of reach for existing algorithms but crucial for RNA functions. LinearTurboFold is a general technique for full-length genome studies and can help fight the current and future pandemics.

bioinformatics↗

bioRxiv2020

Identification of cell-type marker genes from plant single-cell RNA-seq data using machine learning

An essential step in the analysis of single-cell RNA sequencing data is to classify specific cell types with marker genes. In this study, we have developed a machine learning pipeline called Single cell Predictive markers (SPmarker) to identify novel cell-type marker genes in the Arabidopsis root. Unlike traditional approaches, our method uses interpretable machine learning methods to select marker genes. We have demonstrated that our method can (1) assign cell types based on cells that were labeled using published methods, (2) project cell types identified by trajectory analysis from one dataset to other datasets, and (3) assign cell types based on internal GFP markers. Using SPmarker, we have identified hundreds of new marker genes that were not identified before. As compared to known marker genes, we have found more orthologous genes of these new marker genes in corresponding rice single cell clusters. We have also found 172 new marker genes for trichoblast in five non-Arabidopsis species, which expands number of marker genes for this cell type by 35-154%. Our results represent a new approach to identify cell-type marker genes from scRNA-seq data and pave the way for cross-species mapping of scRNA-seq data in plants.

bioinformatics↗

bioRxiv2020

Hydrogel-coating improves the in-vivo stability of electrochemical aptamer-based biosensors

The ability to track the levels of specific molecules, such as drugs, metabolites, and biomarkers, in the living body, in real time and for long durations would improve our understanding of health and our ability to diagnose, treat and monitor disease. To this end, we are developing electrochemical aptamer-based (E-AB) biosensors, a general platform supporting high-frequency, real-time molecular measurements in the living body. Here we report that the addition of an agarose hydrogel protective layer to E-AB sensors significantly improves their baseline stability when deployed in the complex, highly time-varying environments found in vivo. The improved stability is sufficient that these hydrogel-protected sensors achieved good baseline stability when deployed in situ in the veins, muscles, bladder, or tumors of living rats without the use of the drift correction approaches traditionally required in such placements. Finally, this improved stability is achieved without any significant, associated "costs" in terms of detection limits, response times, or biocompatibility.

bioengineering↗

bioRxiv2020

CAMP: a Convolutional Attention-based Neural Network for Multifaceted Peptide-protein Interaction Prediction

Peptide-protein interactions (PepPIs) are involved in various fundamental cellular functions and their identification is crucial for designing efficacious peptide therapeutics. To facilitate the peptide drug discovery process, a number of computational methods have been developed to predict peptide-protein interactions. However, most of the existing prediction approaches heavily depend on high-resolution structure data. Although several deep-learning-based frameworks have been proposed to predict compound-protein interactions or protein-protein interactions, few of them are particularly designed to specifically predict peptide-protein interactions. In this paper, We present a sequence-based Convolutional Attention-based neural network for Multifaceted prediction of Peptide-protein interactions, called CAMP, including predicting binary peptide-protein interactions and corresponding binding residues in the peptides. We also construct a benchmark dataset containing high-quality peptide-protein interaction pairs with the corresponding peptide binding residues for model training and evaluation. CAMP incorporates convolution neural network architectures and attention mechanism to fully exploit informative sequence-based features, including secondary structures, physicochemical properties, intrinsic disorder features and position-specific scoring matrix of the protein. Systematical evaluation of our benchmark dataset demonstrates that CAMP outperforms the state-of-the-art baseline methods on binary peptide-protein interaction prediction. In addition, CAMP can successfully identify the binding residues involved non-covalent interactions for peptides. These results indicate that CAMP can serve as a useful tool in peptide-protein interaction prediction and peptide binding site identification, which can thus greatly facilitate the peptide drug discovery process. The source code of CAMP can be found in https://github.com/twopin/CAMP.

bioinformatics↗

bioRxiv2020

Lipid-specific protein oligomerization is regulated by two interfaces in Marburg virus matrix protein VP40

Marburg virus major matrix protein (mVP40) dimers associate with anionic lipids at the plasma membrane and undergo a dynamic and extensive self-oligomerization into the structural matrix layer which confers the virion shape and stability. Using a myriad of in vitro and cellular techniques, we present a mVP40 assembly model highlighting two distinct oligomerization interfaces (N-terminal domain (NTD) and C-terminal domain (CTD)) in mVP40. Cellular studies of NTD and CTD oligomerization interface mutants demonstrated the importance of each interface in the mVP40 matrix assembly through protein trafficking to the plasma membrane and homo-multimerization that induced protein enrichment, plasma membrane fluidity changes and elongations at the plasma membrane. A novel APEX-TEM method was employed to closely assess the ultrastructural localization of and formation of viral particles for wild type and mutants. Taken together, these studies present a mechanistic model of mVP40 oligomerization and assembly at the plasma membrane during virion assembly.

microbiology↗

bioRxiv2020

Circular RNA as a potential biomarker for forensic age prediction using multiple machine learning models: A preliminary study

In forensic science, accurate estimation of the age of a victim or suspect can facilitate the investigators to narrow a search and aid in solving a crime. Aging is a complex process associated with various molecular regulation on DNA or RNA levels. Recent studies have shown that circular RNAs (circRNAs) upregulate globally during aging in multiple organisms such as mice and elegans because of their ability to resist degradation by exoribonucleases. In the current study, we attempted to investigate circRNAs potential capability of age prediction. Here, we identified more than 40,000 circRNAs in the blood of thirteen Chinese unrelated healthy individuals with ages of 20-62 years according to their circRNA-seq profiles. Three methods were applied to select age-related circRNAs candidates including false discovery rate, lasso regression, and support vector machine. The analysis uncovered a strong bias for circRNA upregulation during aging in human blood. A total of 28 circRNAs were chosen for further validation in 50 healthy unrelated subjects aged between 19 and 72 years by RT-qPCR and finally, 7 age-related circRNAs were chosen for final age prediction models. Several different algorithms including multivariate linear regression (MLR), regression tree, bagging regression, random forest regression (RFR), and support vector regression (SVR) were compared based on root mean square error (RMSE) and mean average error (MAE) values. Among five modeling methods, random forest regression (RFR) performed better than the others with an RMSE value of 5.072 years and an MAE value of 4.065 years (R2 = 0.902). In this preliminary study, we firstly used circRNAs as additional novel age-related biomarkers for developing forensic age estimation models. We propose that the use of circRNAs to obtain additional clues for forensic investigations and serve as aging indicators for age prediction would become a promising field of interest. Author summaryIn forensic investigations, estimation of the age of biological evidence recovered from crime scenes can provide additional information such as chronological age or the appearance of a culprit, which could give valuable investigative leads especially when there is no eyewitness available. Hence, generating an accurate model for age prediction using body fluids such as blood commonly seen at a crime scene can be of vital importance. Various molecular changes on DNA or RNA levels were discovered that they upregulated or downregulated during a persons lifetime. Although some biomarkers have been proved to be associated with aging and used to predict age, several disadvantages such as low sensitivity, prediction accuracy, instability and susceptibility of diseases or immune states, thus limiting their applicability in the field of age estimation. Here, we utilized a novel biomarker namely circular RNA (circRNA) to generate highly accurate age prediction models. We propose that circRNA is more suitable for forensic degradation samples because of its unique molecular structure. This preliminary research offers a new thought for exploring potential biomarker for age prediction.

genetics↗

bioRxiv2020

Identification of Cross-Reactive CD8+ T Cell Receptors with High Functional Avidity to a SARS-CoV-2 Immunodominant Epitope and Its Natural Mutant Variants

Despite the growing knowledge of T cell responses and their epitopes in COVID-19 patients, there is a lack of detailed characterizations for T cell-antigen interactions and T cell functions. Using a peptide library predicted with HLA class I-restriction, specific CD8+ T cell responses were identified in over 75% of COVID-19 convalescent patients. Among the 15 SARS-CoV-2 epitopes identified from the S and N proteins, N361-369 (KTFPPTEPK) was the most dominant epitope. Importantly, we discovered 2 N361-369-specific T cell receptors (TCRs) with high functional avidity, and they exhibited complementary cross-reactivity to reported N361-369 mutant variants. In dendritic cells (DCs) and the lung organoid model, we found that the N361-369 epitope could be processed and endogenously presented to elicit the activation and cytotoxicity of CD8+ T cells ex vivo. Our study evidenced potential mechanisms of cellular immunity to SARS-CoV-2, illuminating natural ways of viral clearance with high relevancy in the vaccine development.

immunology↗

bioRxiv2020

Novel enzyme for dimethyl sulfide-releasing in bacteria reveals a missing route in the marine sulfur cycle

Dimethylsulfoniopropionate (DMSP) is an abundant and ubiquitous organosulfur molecule and plays important roles in the global sulfur cycle. Cleavage of DMSP produces volatile dimethyl sulfide (DMS), which has impacts on the global climate. Multiple pathways for DMSP catabolism have been identified. Here we identified yet another novel pathway, the ATP DMSP lysis pathway. The key enzyme, AcoD, is an ATP-dependent DMSP lyase. AcoD belongs to the acyl-CoA synthetase superfamily, which is totally different from other DMSP lyases, showing a new evolution route. AcoD catalyses the conversion of DMSP to DMS by a two-step reaction: the ligation of DMSP with CoA to form the intermediate DMSP-CoA, which is then cleaved to DMS and acryloyl-CoA. The novel catalytic mechanism was elucidated by structural and biochemical analyses. AcoD is widely distributed in many bacterial lineages including Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria and Firmicutes, revealing this new pathway plays important roles in global DMSP/DMS cycles.

ecology↗

bioRxiv2020

Binding of regulatory proteins to nucleosomes is modulated by dynamic histone tails

Despite histone tails critical roles in epigenetic regulation, little is known about mechanisms of how histone tails modulate the nucleosomal DNA solvent accessibility and recognition of nucleosomes by other macromolecules. Here we generate extensive atomic level conformational ensembles of histone tails in the context of the full human nucleosome, totaling 26 microseconds of molecular dynamics simulations. We explore the histone tail binding with the nucleosomal and linker DNA and observe rapid conformational transitions between bound and unbound states allowing us to estimate kinetic and thermodynamic properties of the histone tail-DNA interactions. Different histone types exhibit distinct, although conformationally heterogeneous, binding modes and each histone type occludes specific DNA regions from the solvent. Using a comprehensive set of experimental data on nucleosome structural complexes, we find that majority of the studied nucleosome-binding proteins and histone tails target mutually exclusive regions on nucleosomal or linker DNA around the super-helical locations {+/-}1, {+/-}2, and {+/-}7. This finding is explained within the generalized competitive binding and tail displacement models of partners recruitment to nucleosomes. Finally, we demonstrate the crosstalk between different histone post-translational modifications, where charge-altering modifications and mutations typically suppress tail-DNA interactions and enhance histone tail dynamics.

biophysics↗

bioRxiv2020

Revisiting the phosphotyrosine binding pocket of Fyn SH2 domain led to the Identification of novel SH2 superbinders

Protein engineering through directed evolution is an effective way to obtain proteins with novel functions with the potential applications as tools for diagnosis or therapeutics. Many natural proteins, largely antibodies as well as some non-antibody proteins, have undergone directed evolution in vitro in the test tubes in the laboratories around the world, resulted in the numerous protein variants with novel or enhanced functions. In this study, we constructed a Fyn SH2 variant library by randomizing the 8 variable residues in its phosphotyrosine (pTyr) binding pocket. Selection of this library by a pTyr peptide from MidT antigen led to the identification of SH2 variants with enhanced affinities to the peptide, compared to the wild type SH2, by EC50 assay. Fluorescent polarization (FP) was then applied to quantify the binding affinity of the newly identified SH2 variants. As a result, three SH2 variants, named V3, V13 and V24, have comparable binding affinities with the previously identified SH2 triple-mutant superbinder (refer to Trm). Biolayer Interferometry (BLI) assay was employed to disclose the kinetics of the binding of these SH2 superbinders, in addition to the wild type SH2, to the phosphotyrosine peptide. The results indicated that all the SH2 superbinders have two-orders increase of the dissociation rate when binding the pTyr peptide while there was no significant change in their associate rates. The previously identified SH2 superbinder Trm as well as the V13 and V24 discovered in this study have cross-reactivity with the sulfotyrosine (sTyr) containing peptide while the wild type SH2 does not. Intriguingly, though binding the pTyr peptide with comparable affinity with other SH2 superbinders, the V3 does not bind to the sTyr peptide, implying it binds to the pTyr peptide with a different pattern from the other superbinders. The newly identified superbinders could be utilized as tools for the identification of pTyr-containing proteins from tissues under different physiological or pathophysiological conditions and may have the potential in the therapeutics.

biochemistry↗

bioRxiv2020

CRISPR-based knockin mutagenesis of the pioneer transcription factor FOXA1; optimization of strategies for multi-allelic proteins in cancer cells

Precise genome engineering of living cells has been revolutionized by the introduction of the highly specific and easily programmable properties of CRISPR-Cas9 technology. This has greatly accelerated research into human health and has facilitated the discovery of novel therapeutics. CRISPR-Cas9 is most widely employed for its ability to inactivate, or knockout, specific genes, but can be also used to introduce subtle site-specific substitutions of DNA sequences that can lead to changes in the amino acid composition of proteins. Despite the proven success of CRISPR-based knockin strategies of genes in typical diploid cells (i.e. cells containing two sets of chromosomes), precise editing of cancer cells, that typically have unstable genomes and multiple copies of chromosomes, is more challenging and not adequately addressed in the literature. Herein we detail our methodology for replacing endogenous proteins with intended knockin mutants in polyploid cancer cells and discuss our experimental design, screening strategy, and facile allele-frequency estimation methodology. As proof of principle, we performed genome editing of specific amino acids within the pioneer transcription factor FOXA1, a critical component of estrogen and androgen receptor signaling, in MCF-7 breast cancer cells. We confirm proper levels of mutant FOXA1 protein expression and intended amino acids substitutions via western blotting and mass spectrometry. In addition, we show that mutant allele-frequency estimation is easily achieved by TOPO cloning combined with allele-specific PCR, which we later confirmed by next-generation RNA-sequencing. Typically, there are 4 - 5 copies (alleles) of FOXA1 in breast cancer cells making the editing of this protein inherently challenging. As a result, most studies that focus on FOXA1 mutants rely on ectopic overexpression of FOXA1 from a plasmid. Therefore, we provide an optimized methodology for replacing endogenous wildtype FOXA1 with precise knockin mutants to enable the systematic analysis of its molecular mechanisms within the appropriate physiological context.

genetics↗

bioRxiv2020

Seipin traps triacylglycerols to facilitate their nanoscale clustering in the ER membrane

Seipin is a disk-like oligomeric ER protein important for lipid droplet (LD) biogenesis and triacylglycerol (TAG) delivery to growing LDs. Here we show through biomolecular simulations bridged to experiments that seipin can trap TAGs in the ER bilayer via the luminal hydrophobic helices of the protomers delineating the inner opening of the seipin disk. This promotes the nanoscale sequestration of TAGs at a concentration that by itself is insufficient to induce TAG clustering in a lipid membrane. We identify Ser166 in the 3 helix as a favored TAG occupancy site and show that mutating it compromises the ability of seipin complexes to sequester TAG in silico and to promote TAG transfer to LDs in cells. While seipin-S166D mutant colocalizes poorly with promethin, the association of nascent wild-type seipin complexes with promethin is promoted by TAGs. Together, these results suggest that seipin traps TAGs via its luminal hydrophobic helices, serving as a catalyst for seeding the TAG cluster from dissolved monomers inside the seipin ring, thereby generating a favorable promethin binding interface.

cell biology↗

bioRxiv2020

BioSamplr: An open source, low cost automated sampling system for bioreactors.

Autosampling from bioreactors reduces error, increases reproducibility and offers improved aseptic handling when compared to manual sampling. Additionally, autosampling greatly decreases the hands-on time required for a bioreactor experiment and enables sampling 24 hrs a day. We have designed, built and tested a low cost, open source, automated bioreactor sampling system, the BioSamplr. The BioSamplr can take up to ten samples from a bioreactor at a desired sample interval and cools them to a desired temperature. The device, assembled from low cost and 3D printed components, is controlled wirelessly by a Raspberry Pi, and records all sampling data to a log file. The cost and accessibility of the BioSamplr make it useful for laboratories without access to more expensive and complex autosampling systems.

bioengineering↗

bioRxiv2020

Experience-dependent alteration of mnemonic representation in early visual cortex and intraparietal sulcus

The ability to discriminate between stimuli relies on a chain of neural operations associated with perception, memory and decision-making. Accumulating studies show learning-dependent plasticity in perception or decision-making, yet whether perceptual learning modifies mnemonic processing remains unclear. Here, we trained participants on an orientation discrimination task, while using fMRI and TMS to separately examine training-induced changes in working memory (WM) representation. Although fMRI decoding revealed orientation-specific neural patterns during delay period in early visual cortex (V1) before, but not after, training, neurodisruption of V1 during delay period led to behavioral deficit in both phases. In contrast, both fMRI decoding and disruptive effect of TMS showed that intraparietal sulcus (IPS) represent WM content after, but not before, training. These results suggest that sensory engagement for WM is relatively independent of training but the coding format may be altered, whereas the involvement of parietal area in WM depends on training.

neuroscience↗

bioRxiv2020

Plasmodium falciparum malaria drives epigenetic reprogramming of human monocytes toward a regulatory phenotype

In malaria-naive children and adults, Plasmodium falciparum-infected red blood cells (Pf-iRBCs) trigger fever and other symptoms of systemic inflammation. However, in endemic areas where individuals experience repeated Pf infections over many years, the risk of Pf-iRBC-triggered inflammatory symptoms decreases with cumulative Pf exposure. The molecular mechanisms underlying these clinical observations remain unclear. Age-stratified analyses of monocytes collected from uninfected, asymptomatic Malian individuals before the malaria season revealed an inverse relationship between age and Pf-iRBC-inducible inflammatory cytokine (IL-1{beta}, IL-6 and TNF) production, whereas Malian infants and malaria-naive U.S. adults produced similarly high levels of inflammatory cytokines. Accordingly, monocytes of Malian adults produced more IL-10 and expressed higher levels of the regulatory molecules CD163, CD206, Arginase-1 and TGM2. These observations were recapitulated in an in vitro system of monocyte to macrophage differentiation wherein macrophages re-exposed to Pf-iRBCs exhibited attenuated inflammatory cytokine responses and a corresponding decrease in the epigenetic marker of active gene transcription, H3K4me3, at inflammatory cytokine gene loci. Together these data indicate that Pf induces epigenetic reprogramming of monocytes/macrophages toward a regulatory phenotype that attenuates inflammatory responses during subsequent Pf exposure. These findings also suggest that past malaria exposure could mitigate monocyte-associated immunopathology induced by other pathogens such as SARS-CoV-2. Author SummaryThe malaria parasite is mosquito-transmitted and causes fever and other inflammatory symptoms while circulating in the bloodstream. However, in regions of high malaria transmission the parasite is less likely to cause fever as children age and enter adulthood, even though adults commonly have malaria parasites in their blood. Monocytes are cells of the innate immune system that secrete molecules that cause fever and inflammation when encountering microorganisms like malaria. Although inflammation is critical to initiating normal immune responses, too much inflammation can harm infected individuals. In Mali, we conducted a study of a malaria-exposed population from infants to adults and found that participants monocytes produced less inflammation as age increases, whereas monocytes of Malian infants and U.S. adults, who had never been exposed to malaria, both produced high levels of inflammatory molecules. Accordingly, monocytes exposed to malaria in the laboratory became less inflammatory when re-exposed to malaria again later, and these monocytes turned down their inflammatory genes. This study helps us understand how people become immune to inflammatory symptoms of malaria and may also help explain why people in malaria-endemic areas appear to be less susceptible to the harmful effects of inflammation caused by other pathogens such as SARS-CoV-2.

immunology↗

bioRxiv2020

Expression analysis of photosynthesis-related genes in albino Artocarpus heterophyllus seedlings leaves

Albino Artocarpus heterophyllus Seedlings (AAS) were found in the preliminary investigation by our group and were used as materials for researching. The phenotype of AAS leaves were observed and measured. In parallel, the photosynthetic physiological parameters were determined under different photosynthetically active radiations (PAR). The results suggested that the length, width, area and thickness of AAS leaves were less than normal seedings. Likewise, the net photosynthetic rate, intercellular CO2 concentration, stomatal conductance and transpiration rate of AAS leaves were not susceptible to PAR in contrast to normal individuals. Furthermore, the transcriptome sequencing technology was performed to clarify the expression of genes related to photosynthesis. It is as expected that numerous down-regulated genes were found in the synthesis of photosynthetic pigments, as well as the pathways of photosynthesis - antenna proteins, photoreaction and carbon fixation reaction of AAS leaves. Compared to other albino plants, AAS have a longer life span and more stable phenotypic traits with larger leaves, which could provide ideal materials for investigating photosynthesis of woody plants.

physiology↗

bioRxiv2020

Pore constrictions in intervessel pit membranes reduce the risk of embolism spreading in angiosperm xylem

O_LIEmbolism spreading in angiosperm xylem occurs via mesoporous pit membranes between vessels. Here, we investigate how the size of pore constrictions in pit membranes is related to pit membrane thickness and embolism resistance. C_LIO_LIIn three models, pit membranes are modelled as multiple layers to investigate how pit membrane thickness and the number of intervessel pits per vessel determine pore constriction sizes, the probability of encountering large pores, and air-seeding. These estimations were complemented by measurements of pit membrane thickness, embolism resistance, and number of intervessel pits per vessel (n = 31, 31, and 20 species, respectively). C_LIO_LIConstriction sizes in pores decreased with increasing pit membrane thickness, which agreed with the measured relationship between pit membrane thickness and embolism resistance. The number of pits per vessel affected constriction size and embolism resistance much less than pit membrane thickness. A strong relationship between estimated air-seeding pressures and measured embolism resistance was observed. C_LIO_LIPore constrictions provide a mechanistic explanation why pit membrane thickness determines embolism resistance, and suggest that hydraulic safety can be uncoupled from hydraulic efficiency. Although embolism spreading remains puzzling and encompasses more than pore constriction sizes, angiosperms are unlikely to have leaky pit membranes, which enables tensile transport of water. C_LI

plant biology↗