Biology subjects

Zhou, G.

Publications and source records attributed to Zhou, G..

8 recordsLinked to original sources

bioRxiv2018

The saturation gap: a simple transformation of oxygen saturation using virtual shunt

ObjectivePeripheral oxygen saturation (SpO2) obtained from pulse oximetry is a widely used physiological measurement. Clinical interpretation is limited by the nonlinear relationship between SpO2, degree of impairment in gas exchange, and effect of altitude. SpO2 is frequently dichotomized to overcome these limitations during prediction modelling. Using the known physiological relationship between virtual shunt and SpO2, we propose the saturation gap as a transformation of SpO2.\n\nApproachWe computed the theoretical virtual shunt corresponding to various SpO2 values and derived an accurate approximation formula between virtual shunt and SpO2. The approximation was based on previously described empiric observations and known physiological relationships. We evaluated the utility of the saturation gap in a clinical study predicting the need for facility admission in children in a rural health-care setting.\n\nMain ResultsThe transformation was saturation gap = 49.314*log10(103.711 - SpO2) -37.315. The ability to predict hospital admission based on a continuous variable SpO2 or saturation gap produced an identical area under the curve of 0.71 (95% CI: 0.69-0.73), compared to only 0.57 (CI: 0.56-0.58) based on diagnosis of hypoxemia (defined as SpO2<90%). However, SpO2 demonstrated a lack of fit compared to saturation gap (goodness-of-fit test p-value <0.0001 versus 0.098). The observed admission rates varied linearly with saturation gap but varied nonlinearly with SpO2.\n\nSignificanceThe saturation gap estimates a continuous linearly interpretable disease severity from SpO2 and improves clinical prediction models. The saturation gap will also allow for straightforward incorporation of altitude in interpretation of measurements of SpO2.

bioengineering↗

bioRxiv2018

Metabolically activated macrophages in mammary adipose tissue link obesity to triple-negative breast cancer

Obesity is associated with increased incidence and severity of triple-negative breast cancer (TNBC); however, mechanisms underlying this relationship are incompletely understood. Macrophages, which accumulate in adipose tissue and are activated during obesity, are an attractive mechanistic link. Here, we show that, during obesity, murine and human mammary adipose tissue macrophages adopt a pro-inflammatory, metabolically- activated (MMe) macrophage phenotype that promotes TNBC stem-like markers and functions, including increased tumorsphere growth in vitro and tumor-initiating potential in vivo. We demonstrate that MMe macrophages release cytokines in an NADPH oxidase 2 (NOX2)-dependent manner that signal through glycoprotein 130 (GP130) on TNBC cells to promote their stem-like properties. Accordingly, deleting Nox2 in myeloid cells or depleting GP130 in TNBC cells attenuates the ability of obesity to drive TNBC tumor formation. Our studies implicate MMe macrophage accumulation in mammary adipose tissue during obesity as a mechanism for promoting TNBC stemness and tumorigenesis.\n\nHIGHLIGHTS Obesity promotes TNBC tumor formation and stemness.\nMammary adipose tissue macrophages are metabolically activated (MMe) in obese mice and humans.\nMMe macrophages in mammary adipose tissue contribute to obesity-induced stemness.\nMMe macrophages promote TNBC stemness through GP130 signaling.

cancer biology↗

bioRxiv2018

Rice Galaxy: an open resource for plant science

Background\n\nRice molecular genetics, breeding, genetic diversity, and allied research (such as rice-pathogen interaction) have adopted sequencing technologies and high density genotyping platforms for genome variation analysis and gene discovery. Germplasm collections representing rice diversity, improved varieties and elite breeding materials are accessible through rice gene banks for use in research and breeding, with many having genome sequences and high density genotype data available. Combining phenotypic and genotypic information on these accessions enables genome-wide association analysis, which is driving quantitative trait loci (QTL) discovery and molecular marker development. Comparative sequence analyses across QTL regions facilitate the discovery of novel alleles. Analyses involving DNA sequences and large genotyping matrices for thousands of samples, however, pose a challenge to non-computer savvy rice researchers.\n\nFindings\n\nWe adopted the Galaxy framework to build the federated Rice Galaxy resource, with shared datasets, tools, and analysis workflows relevant to rice research. The shared datasets include high density genotypes from the 3,000 Rice Genomes project and sequences with corresponding annotations from nine published rice genomes. Rice Galaxy includes tools for designing single nucleotide polymorphism (SNP) assays, analyzing genome-wide association studies, population diversity, rice-bacterial pathogen diagnostics, and a suite of published genomic prediction methods. A prototype Rice Galaxy compliant to Open Access, Open Data, and Findable, Accessible, Interoperable, and Reproducible principles is also presented.\n\nConclusions\n\nRice Galaxy is a freely available resource that empowers the plant research community to perform state-of-the-art analyses and utilize publicly available big datasets for both fundamental and applied science.

bioinformatics↗

bioRxiv2018

Base pair editing of goat embryos: nonsense codon introgression into FGF5 to improve cashmere yield

The ability to alter single bases without DNA double strand breaks provides a potential solution for multiplex editing of livestock genomes for quantitative traits. Here, we report using a single base editing system, Base Editor 3 (BE3), to induce nonsense codons (C-to-T transitions) at four target sites in caprine FGF5. All five progenies produced from microinjected single-cell embryos had alleles with a targeted nonsense mutation and yielded expected phenotypes. The effectiveness of BE3 to make single base changes varied considerably based on sgRNA design. Also, the rate of mosaicism differed between animals, target sites, and tissue type. PCR amplicon and whole genome resequencing analyses for off-target changes caused by BE3 were low at a genome-wide scale. This study provides first evidence of base editing in livestock, thus presenting a potentially better method to introgress complex human disease alleles into large animal models and provide genetic improvement of complex health and production traits in a single generation.

genetics↗

bioRxiv2018

Base-pair Ambiguity and the Kinetics of RNA Folding: a Hypothesis-Driven Statistical Analysis

BackgroundA folding RNA molecule encounters multiple opportunities to form non-native yet energetically favorable pairings of nucleotide sequences. Given this forbidding free-energy landscape, mechanisms have evolved that contribute to a directed and efficient folding process, including catalytic proteins and error-detecting chaperones. Among structural RNA molecules we make a distinction between \"bound\" molecules, which are active as part of ribonucleoprotein (RNP) complexes, and \"unbound,\" with physiological functions performed without necessarily being bound in RNP complexes. We hypothesized that unbound molecules, lacking the partnering structure of a protein, would be more vulnerable than bound molecules to kinetic traps that compete with native stem structures. We defined an \"ambiguity index\"--a normalized function of the primary and secondary structure of an individual molecule that measures the number of kinetic traps available to nucleotide sequences that are paired in the native structure, presuming that unbound molecules would have lower indexes. The ambiguity index depends on the purported secondary structure, and was computed under both the comparative (\"gold standard\") and an equilibrium-based prediction which approximates the minimum free energy (MFE) structure. Arguing that kinetically accessible metastable structures might be more biologically relevant than thermodynamic equilibrium structures, we also hypothesized that MFE-derived ambiguities would be less effective in separating bound and unbound molecules.\n\nResultsWe have introduced an intuitive and easily computed function of primary and secondary structures that measures the availability of complementary sequences that could disrupt the formation of native stems on a given molecule--an ambiguity index. Using comparative secondary structures, the ambiguity index is systematically smaller among unbound than bound molecules, as expected. Furthermore, the effect is lost when the presumably more accurate comparative structure is replaced instead by the MFE structure.\n\nConclusionsA statistical analysis of the relationship between the primary and secondary structures of non-coding RNA molecules suggests that stem-disrupting kinetic traps are substantially less prevalent in molecules not participating in RNP complexes. In that this distinction is apparent under the comparative but not the MFE secondary structure, the results highlight a possible deficiency in structure predictions when based upon assumptions of thermodynamic equilibrium.

bioinformatics↗

bioRxiv2018

Temporal changes in gut microbiota and signaling molecules of the gut-brain axis in mice fed meat protein diets

The purpose of this study was to characterize the dynamical changes of gut microbiota and explore the influence on bidirectional communications between the gut and the brain during a relatively long-term intake of different protein diets. The C57BL/6J mice were fed casein, soy protein and four kinds of processed meat proteins at a normal dose of 20% for 8 months. Protein diets dramatically affected the microbial composition and function and also the signaling molecule levels of the gut-brain axis in a dynamic manner, which consequently affected growth performance. Alistipes, Clostridiales vadinBB60, Anaerotruncus, Blautia and Oscillibacter had a relatively fast response to the diet, while Bacteroidales S24-7, Ruminiclostridium, Ruminococcaceae UCG-014, Coriobacteriaceae UCG-002 and Bilophila responded slowly. Rikenellaceae RC9 gut, Faecalibaculum and Lachnospiraceae showed a continuous change with feeding time. Bacteroidales S24-7 abundance increased from 4 months to 8 months, whereas those of Rikenellaceae RC9 gut, Akkermansia, Alistipes and Anaerotruncus remarkably decreased. Five and fifteen biological functions of microbiota were affected at 4 months and 8 months, respectively, and sixteen functions were observed to change over feeding time. Moreover, 28 and 48 specific operational taxonomy units were associated with the regulation of serotonin, peptide YY, leptin and insulin levels at two time points. Ruminococcaceae was positively associated with Lachnospiraceae and negatively associated with Bacteroidales S24-7. These results give an important insight into the effect of gut microbiota on the bidirectional communications between the gut and the brain under a certain type of diet.\n\nImportanceMany gastrointestinal and neuropsychiatric disorders may have a common pathophysiologic mechanism, involving bidirectional brain-gut axis signaling through humoral and neural pathways. The gut microbiota plays an important role in the communications between the gut and the brain. Recent evidence suggests that a growing number of subjects suffer from the above disorders. The significance of this study lies in the finding that long-term intake of different proteins at a normal dose induces dynamic alterations of specific microbiota in mice, which consequently affect bidirectional communications between the gut and the brain and results in different growth performance through dynamically regulating signaling molecule levels. Furthermore, this study indicates that intake of the same diet for a long time, irrespective of the diet source, may have an adverse effect on host health by altering gut microbiota.

microbiology↗

bioRxiv2017

Maize leaf functional responses to drought episode and rewatering

Effects of crop growth and physiological activity to drought and irrigation regimes have been extensively studied; however, the responses of plant growth, morphological and photosynthetic behaviors to drought episodes and thereafter rewatering receive a less attention. This field experiment was carried out directly in situ at an agricultural ecosystem research station during 2015-2016, in a northeastern China, on the renowned northeastern maize production belt, where is being threatened by severe drought. A field automatic rain-shelter was used, and five irrigation regimes including control, four drought episodes, and rewatering treatments were established. The chlorophyll contents (SPAD values), light-saturated photosynthetic rate (Asat), and photosystem II actual quantum yield ({Phi}PSII), maximum quantum yield (Fv'/Fm') decreased at lower leaf positions and with plant development. Episodic drought effects on plant growth, leaf morphological traits and photosynthetic processes at both vegetative and reproductive stages were severely remarked, particularly at late development stage and with longer drought duration. The recovery of leaf functional traits of the plants experienced historical-drought following re-irrigating was not fully restored to the level of the plants subjected to ample and normal water status; and the strength of recovery was proportional to the persistence of pre-drought episodes. The relationship of Asat with SPAD depends on water status and plant development. A principal component analysis can well denote the change patterns in responses to water status treatments with plant development. The results may give an insight into how to understand the maize traits responses to drought episode and rewatering, and this also might assist the drought-stricken crops to cope with future climatic change.

plant biology↗

bioRxiv2016

Bridging microscopic and macroscopic mechanisms of p53-MDM2 binding using molecular simulations and kinetic network models

Under normal cellular conditions, the tumor suppressor protein p53 is kept at a low levels in part due to ubiquitination by MDM2, a process initiated by binding of MDM2 to the intrinsically disordered transactivation domain (TAD) of p53. Although many experimental and simulation studies suggest that disordered domains such as p53 TAD bind their targets nonspecifically before folding to a tightly-associated conformation, the molecular details are unclear. Toward a detailed prediction of binding mechanism, pathways and rates, we have performed large-scale unbiased all-atom simulations of p53-MDM2 binding. Markov State Models (MSMs) constructed from the trajectory data predict p53 TAD peptide binding pathways and on-rates in good agreement with experiment. The MSM reveals that two key bound intermediates, each with a non-native arrangement of hydrophobic residues in the MDM2 binding cleft, control the overall on-rate. Using microscopic rate information from the MSM, we parameterize a simple four-state kinetic model to (1) determine that induced-fit pathways dominate the binding flux over a large range of concentrations, and (2) predict how modulation of residual p53 helicity affects binding, in good agreement with experiment. These results suggest new ways in which microscopic models of bound-state ensembles can be used to understand biological function on a macroscopic scale.\n\nAUTHOR SUMMARYMany cell signaling pathways involve protein-protein interactions in which an intrinsically disordered peptide folds upon binding its target. Determining the molecular mechanisms that control these binding rates is important for understanding how such systems are regulated. In this paper, we show how extensive all-atom simulations combined with kinetic network models provide a detailed mechanistic understanding of how tumor suppressor protein p53 binds to MDM2, an important target of new cancer therapeutics. A simple four-state model parameterized from the simulations shows a binding-then-folding mechanism, and recapitulates experiments in which residual helicity boosts binding. This work goes beyond previous simulations of small-molecule binding, to achieve pathways and binding rates for a large peptide, in good agreement with experiment.

biophysics↗