Establishment of real-time fluorescence and visual LAMP for rapid detection of Escherichia coli O157:H7 and kits construction.

Escherichia coli O157:H7 is a common pathogenic bacterium in food and water that can pose a threat to human health. The aim of this study was to develop loop-mediated isothermal amplification (LAMP) method for the detection of E. coli O157:H7 in food based on the specific gene Ecs_2840 and to construct rapid detection kits based on the established methods. Specifically, we established two methods of real-time fluorescent LAMP (RT-LAMP) and visual LAMP with calcein as an indicator. In pure bacterial culture, the cell sensitivity and genomic sensitivity of the RT-LAMP kit were 8.8 × 100 CFU ml-1 and 4.61 fg µl-1, respectively. The sensitivity of the visual LAMP kit was 2.35 × 100 CFU ml-1 and 4.61 fg µl-1. Both kits had excellent specificity and anti-interference performance. In addition, milk inoculated with 2.26 × 100 CFU ml-1E. coli O157:H7 could be detected within the reaction time after enrichment for 3 h. The results showed that the LAMP kits were rapid, sensitive, and specific for the detection of E. coli O157:H7 in food and had good application prospects in food safety surveillance.

Learning from real world data about combinatorial treatment selection for COVID-19.

COVID-19 is an unprecedented global pandemic with a serious negative impact on virtually every part of the world. Although much progress has been made in preventing and treating the disease, much remains to be learned about how best to treat the disease while considering patient and disease characteristics. This paper reports a case study of combinatorial treatment selection for COVID-19 based on real-world data from a large hospital in Southern China. In this observational study, 417 confirmed COVID-19 patients were treated with various combinations of drugs and followed for four weeks after discharge (or until death). Treatment failure is defined as death during hospitalization or recurrence of COVID-19 within four weeks of discharge. Using a virtual multiple matching method to adjust for confounding, we estimate and compare the failure rates of different combinatorial treatments, both in the whole study population and in subpopulations defined by baseline characteristics. Our analysis reveals that treatment effects are substantial and heterogeneous, and that the optimal combinatorial treatment may depend on baseline age, systolic blood pressure, and c-reactive protein level. Using these three variables to stratify the study population leads to a stratified treatment strategy that involves several different combinations of drugs (for patients in different strata). Our findings are exploratory and require further validation.

Study of the distribution of Glycyrrhiza uralensis production areas as well as the factors affecting yield and quality.

Wild licorice in China is mainly distributed in northern China, such as Gansu, Ningxia, and Inner Mongolia Provinces. The origin of wild licorice has varied among historical periods. The cultivated origin of planted licorice has the same as 59.26% of wild licorice. The distribution of cultivated licorice was shifted to the northwest relative to that of wild licorice. The yield and quality of cultivated licorice vary greatly from different origins, showing a certain pattern of variation from west to east. The same batch of licorice seedlings was planted at 8 sites overlapping the main licorice production areas in China. The yield and quality of licorice in the Baicheng experimental plot were low. The yield of licorice in the Jingtai and Altay experimental plots was high, but the quality was poor. The quality of licorice in Chifeng and Yuzhong experimental sites was high, but the yield was low. Principal component analysis of environmental and soil factors generated five characteristic roots with a cumulative contribution rate of 80%, three of which were related to soil and referred to as the soil charge factor, soil water factor, and soil nutrient factor, and the load coefficients of the water and nutrient factor were the largest. Soil conditions, especially water and nutrients, might have a substantial effect on the observed changes in the licorice production area. Generally, the regulation of water and nutrients merits special attention when selecting areas for the production and cultivation of licorice. This study can provide reference for the selection of cultivated licorice production areas and the research of high-quality cultivation techniques.

Learning Interactions in Reaction Diffusion Equations by Neural Networks.

Partial differential equations are common models in biology for predicting and explaining complex behaviors. Nevertheless, deriving the equations and estimating the corresponding parameters remains challenging from data. In particular, the fine description of the interactions between species requires care for taking into account various regimes such as saturation effects. We apply a method based on neural networks to discover the underlying PDE systems, which involve fractional terms and may also contain integration terms based on observed data. Our proposed framework, called Frac-PDE-Net, adapts the PDE-Net 2.0 by adding layers that are designed to learn fractional and integration terms. The key technical challenge of this task is the identifiability issue. More precisely, one needs to identify the main terms and combine similar terms among a huge number of candidates in fractional form generated by the neural network scheme due to the division operation. In order to overcome this barrier, we set up certain assumptions according to realistic biological behavior. Additionally, we use an L2-norm based term selection criterion and the sparse regression to obtain a parsimonious model. It turns out that the method of Frac-PDE-Net is capable of recovering the main terms with accurate coefficients, allowing for effective long term prediction. We demonstrate the interest of the method on a biological PDE model proposed to study the pollen tube growth problem.

[Effects of pH value on stachydrine biosynthesis of hydroponic Leonurus japonicus and its physiological mechanism].

The present study explored the physiological mechanism of the effects of different pH treatments on the growth, physiological characteristics, and stachydrine biosynthesis of Leonurus japonicus to provide references for the cultivation and quality control of L. japonicus. Under hydroponic conditions, different pH treatments(pH 5,6,7,8) were set up. The growth, physiology, and the content of stachydrine and total alkaloids of L. japonicus, as well as the content of key intermediate products in stachydrine biosynthesis pathway(i.e., pyruvic acid, α-ketoglutaric acid, glutamic acid, and ornithine) were monitored to explore the physiological mechanism of the effects of pH on the growth and active components of L. japonicus. The results showed that L. japonicus. could grow normally in the pH 5-8 solution. The pH treatment of neutral acidity was more conducive to the accumulation of photosynthetic pigments and the increase in soluble protein in leaves of L. japonicus. to promote its growth and yield. However, since stachydrine is a nitrogen-containing pyrrolidine alkaloid, its synthesis involves the two key rate-limiting steps of nitrogen addition: reductive ammoniation reaction and Schiff base formation reaction. High pH treatments promote the synthesis and accumulation of substrates and products of the above two reactions, indicating that the alkaline environment can promote the nitrogen addition reaction, thereby promoting the biosynthesis and accumulation of stachydrine.

Constrained Nonlinear and Mixed Effects Integral Differential Equation Models for Dynamic Cell Polarity Signaling.

Polar cell growth is a process that couples the establishment of cell polarity with growth and is extremely important in the growth, development, and reproduction of eukaryotic organisms, such as pollen tube growth during plant fertilization and neuronal axon growth in animals. Pollen tube growth requires dynamic but polarized distribution and activation of a signaling protein named ROP1 to the plasma membrane via three processes: positive feedback and negative feedback regulation of ROP1 activation and its lateral diffusion along the plasma membrane. In this paper, we introduce a mechanistic integro-differential equation (IDE) along with constrained semiparametric regression to quantitatively describe the interplay among these three processes that lead to the polar distribution of active ROP1 at a steady state. Moreover, we introduce a population variability by a constrained nonlinear mixed model. Our analysis of ROP1 activity distributions from multiple pollen tubes revealed that the equilibrium between the positive and negative feedbacks for pollen tubes with similar shapes are remarkably stable, permitting us to infer an inherent quantitative relationship between the positive and negative feedback loops that defines the tip growth of pollen tubes and the polarity of tip growth.

CamelliA-based simultaneous imaging of Ca2+ dynamics in subcellular compartments.

As a universal second messenger, calcium (Ca2+) transmits specific cellular signals via a spatiotemporal signature generated from its extracellular source and internal stores. Our knowledge of the mechanisms underlying the generation of a Ca2+ signature is hampered by limited tools for simultaneously monitoring dynamic Ca2+ levels in multiple subcellular compartments. To overcome the limitation and to further improve spatiotemporal resolutions, we have assembled a molecular toolset (CamelliA lines) in Arabidopsis (Arabidopsis thaliana) that enables simultaneous and high-resolution monitoring of Ca2+ dynamics in multiple subcellular compartments through imaging different single-colored genetically encoded calcium indicators. We uncovered several Ca2+ signatures in three types of Arabidopsis cells in response to internal and external cues, including rapid oscillations of cytosolic Ca2+ and apical plasma membrane Ca2+ influx in fast-growing Arabidopsis pollen tubes, the spatiotemporal relationship of Ca2+ dynamics in four subcellular compartments of root epidermal cells challenged with salt, and a shockwave-like Ca2+ wave propagating in laser-wounded leaf epidermis. These observations serve as a testimony to the wide applicability of the CamelliA lines for elucidating the subcellular sources contributing to the Ca2+ signatures in plants.

Machine Learning Aids Classification and Discrimination of Noncanonical DNA Folding Motifs by an Arrayed Host:Guest Sensing System.

An arrayed host:guest fluorescence sensor system can discriminate among and classify multiple different noncanonical DNA structures by exploiting selective molecular recognition. The sensor is highly selective and can discriminate between folds as similar as native G-quadruplexes and those with bulges or vacancies. The host and guest can form heteroternary complexes with DNA strands, with the host acting as mediator between the DNA and dye, modulating the emission. By applying machine learning algorithms to the sensing data, prediction of the folding state of unknown DNA strands is possible with high fidelity.

Diverse Intercropping Patterns Enhance the Productivity and Volatile Oil Yield of Atractylodes lancea (Thunb.) DC.

Commercial cultivation of the medicinal plant Atractylodes lancea is significantly restricted by low survival rates and reduced yields. Intercropping can reasonably coordinate interspecific interactions, effectively utilize environmental resources, and increase survival and yield. We conducted a field experiment from 2014 to 2016 to analyze the advantages and effects of intercropping on A. lancea survival, growth traits, individual volatile oil content, and total volatile oil content. In addition to A. lancea monoculture (AL), five intercropping combinations were planted: Zea mays L. (ZM) + A. lancea, Tagetes erecta L. (TE) + A. lancea, Calendula officinalis L. (CO) + A. lancea, Glycine max (Linn.) Merr. (GM) + A. lancea, and Polygonum hydropiper L. (PH) + A. lancea. The survival and average rhizome weight of A. lancea was higher in the ZM, CO, and TE treatments than in the monoculture treatment, and the average plant height was higher in all intercropping treatments than in the monoculture. The volatile oil content of A. lancea from the ZM and CO treatments was significantly improved relative to that of monoculture plants. The volatile oil harvest was higher in the ZM, CO, and TE treatments than in the monoculture. We conclude that intercropping is an effective way to increase the survival and yield of A. lancea. Furthermore, intercropping with ZM, CO, and TE increases the harvest of four volatile oils from A. lancea.

Calibration-free analysis of surface proteins on single extracellular vesicles enabled by DNA nanostructure.

Extracellular vesicles (EVs) are essential intercellular communicators that are of increasing interest as diagnostic biomarkers. Exploring their biological functions and clinical values, however, remains challenging due to their small sizes and high heterogeneity. Herein, we report an ultrasensitive method that employs target-initiated construction of DNA nanostructure to detect single EVs with an input as low as 100 vesicles/µL. Taking advantage of both DNA nanostructure labeling and EV membrane staining, the method can also permit calibration-free analysis of the protein profiles among different EV samples, leading to clear EV differentiation by their cell of origin. Moreover, this method allows co-localization of dual protein markers on the same EV, and the increased number of EVs carrying dual tumor proteins present in human serum could differentiate cancer patients at the early developmental stage from healthy controls. Our results demonstrate the great potential of this single-EV visualization method in non-invasive detection of the EV-based protein biomarkers for cancer diagnosis and treatment monitoring.

The chromatin-remodeling protein BAF60/SWP73A regulates the plant immune receptor NLRs.

In both plant and animal innate immune responses, surveillance of pathogen infection is mediated by membrane-associated receptors and intracellular nucleotide-binding domain and leucine-rich-repeat receptors (NLRs). Homeostasis of NLRs is under tight multilayered regulation to avoid over-accumulation or over-activation, which often leads to autoimmune responses that have detrimental effects on growth and development. How NLRs are regulated epigenetically at the chromatin level remains unclear. Here, we report that SWP73A, an ortholog of the mammalian switch/sucrose nonfermentable (SWI/SNF) chromatin-remodeling protein BAF60, suppresses the expression of NLRs either directly by binding to the NLR promoters or indirectly by affecting the alternative splicing of some NLRs through the suppression of cell division cycle 5 (CDC5), a key regulator of RNA splicing. Upon infection, bacteria-induced small RNAs silence SWP73A to activate a group of NLRs and trigger robust immune responses. SWP73A may function as a H3K9me2 reader to enhance transcription suppression.

Menthol in electronic cigarettes: A contributor to respiratory disease?

Menthol is widely used in tobacco products. This study compared the effects of menthol on human bronchial epithelium using submerged cultures, a VITROCELL® cloud chamber that provides air liquid interface (ALI) exposure without solvents or heating, and a Cultex ALI system that delivers aerosol equivalent to that inhaled during vaping. In submerged culture, menthol significantly increased calcium influx and mitochondrial reactive oxygen species (ROS) via the TRPM8 receptor, responses that were inhibited by a TRPM8 antagonist. VITROCELL® cloud chamber exposure of BEAS-2B monolayers increased mitochondrial protein oxidation, expression of the antioxidant enzyme SOD2, activation of NF-κB, and secretion of inflammatory cytokines (IL-6 and IL-8). Proteomics data collected following ALI exposure of 3D EpiAirway tissue in the Cultex showed upregulation of NRF-2-mediated oxidative stress, oxidative phosphorylation, and IL-8 signaling. Across the three platforms, menthol adversely effected human bronchial epithelium in a manner that could lead to respiratory disease.

DNA methylation markers in the diagnosis and prognosis of common leukemias.

The ability to identify a specific type of leukemia using minimally invasive biopsies holds great promise to improve the diagnosis, treatment selection, and prognosis prediction of patients. Using genome-wide methylation profiling and machine learning methods, we investigated the utility of CpG methylation status to differentiate blood from patients with acute lymphocytic leukemia (ALL) or acute myelogenous leukemia (AML) from normal blood. We established a CpG methylation panel that can distinguish ALL and AML blood from normal blood as well as ALL blood from AML blood with high sensitivity and specificity. We then developed a methylation-based survival classifier with 23 CpGs for ALL and 20 CpGs for AML that could successfully divide patients into high-risk and low-risk groups, with significant differences in clinical outcome in each leukemia type. Together, these findings demonstrate that methylation profiles can be highly sensitive and specific in the accurate diagnosis of ALL and AML, with implications for the prediction of prognosis and treatment selection.

Constructing confidence intervals for selected parameters.

In large-scale problems, it is common practice to select important parameters by a procedure such as the Benjamini and Hochberg procedure and construct confidence intervals (CIs) for further investigation while the false coverage-statement rate (FCR) for the CIs is controlled at a desired level. Although the well-known BY CIs control the FCR, they are uniformly inflated. In this paper, we propose two methods to construct shorter selective CIs. The first method produces shorter CIs by allowing a reduced number of selective CIs. The second method produces shorter CIs by allowing a prefixed proportion of CIs containing the values of uninteresting parameters. We theoretically prove that the proposed CIs are uniformly shorter than BY CIs and control the FCR asymptotically for independent data. Numerical results confirm our theoretical results and show that the proposed CIs still work for correlated data. We illustrate the advantage of the proposed procedures by analyzing the microarray data from a HIV study.

Spatiotemporal dynamics of a reaction-diffusion model of pollen tube tip growth.

A reaction-diffusion model is proposed to describe the mechanisms underlying the spatial distributions of ROP1 and calcium on the pollen tube tip. The model assumes that the plasma membrane ROP1 activates itself through positive feedback loop, while the cytosolic calcium ions inhibit ROP1 via a negative feedback loop. Furthermore it is proposed that lateral movement of molecules on the plasma membrane are depicted by diffusion. It is shown that bistable or oscillatory dynamics could exist even in the non-spatial model, and stationary and oscillatory spatiotemporal patterns are found in the full spatial model which resemble the experimental data of pollen tube tip growth.

Strain-GeMS: optimized subspecies identification from microbiome data based on accurate variant modeling.

MOTIVATION: Subspecies identification is one of the most critical issues in microbiome studies, as it is directly related to their functions in response to the environmental stress and their feedbacks. However, identification of subspecies remains a challenge largely due to the small variation between different strains within the same species. Accurate identification of subspecies primarily relies on variant identification and categorization through microbiome data. However, current SNP calling and subspecies identification for microbiome data remain underdeveloped. RESULTS: In this work, we have proposed Strain-GeMS for subspecies identification from microbiome data, based on solid statistical model for SNP calling, as well as optimized procedure for subspecies identification. Results on simulated, ab initio and in vivo datasets have shown that Strain-GeMS could always generate more accurate results compared with other subspecies identification methods. AVAILABILITY AND IMPLEMENTATION: Strain-GeMS is available at: https://github.com/HUST-NingKang-Lab/straingems. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Exocytosis-coordinated mechanisms for tip growth underlie pollen tube growth guidance.

Many tip-growing cells are capable of responding to guidance cues, during which cells precisely steer their growth toward the source of guidance signals. Though several players in signal perception have been identified, little is known about the downstream signaling that controls growth direction during guidance. Here, using combined modeling and experimental studies, we demonstrate that the growth guidance of Arabidopsis pollen tubes is regulated by the signaling network that controls tip growth. Tip-localized exocytosis plays a key role in this network by integrating guidance signals with the ROP1 Rho GTPase signaling and coordinating intracellular signaling with cell wall mechanics. This model reproduces the high robustness and responsiveness of pollen tube guidance and explains the connection between guidance efficiency and the parameters of the tip growth system. Hence, our findings establish an exocytosis-coordinated mechanism underlying the cellular pathfinding guided by signal gradients and the mechanistic linkage between tip growth and guidance.

Silencing of AtRAP, a target gene of a bacteria-induced small RNA, triggers antibacterial defense responses through activation of LSU2 and down-regulation of GLK1.

Plants fine-tune their sophisticated immunity systems in response to pathogen infections. We previously showed that AtlsiRNA-1, a bacteria-induced plant endogenous small interfering RNA, silences the AtRAP gene, which encodes a putative RNA binding protein. In this study, we demonstrate that AtRAP functions as a negative regulator in plant immunity by characterizing molecular and biological responses of the knockout mutant and overexpression lines of AtRAP upon bacterial infection. AtRAP is localized in chloroplasts and physically interacts with Low Sulfur Upregulated 2 (LSU2), which positively regulates plant defense. Our results suggest that AtRAP negatively regulates defense responses by suppressing LSU2 through physical interaction. We also detected downregulation of the transcription factor GOLDEN2-LIKE 1 (GLK1) in atrap-1 using microarray analysis. The glk1 glk2 double mutant showed enhanced resistance to Pseudomonas syringae pv. tomato, which is consistent with a previous study showing enhanced resistance of a glk1 glk2 double mutant to Hyaloperonospora arabidopsidis. Taken together, our data suggest that silencing of AtRAP by AtlsiRNA-1 upon bacterial infection triggers defense responses through regulation of LSU2 and GLK1.