Biology subjects

Guo, C.

Publications and source records attributed to Guo, C..

11 recordsLinked to original sources

bioRxiv2018

Genetic population variation and phylogeny of Sinomenium acutum (Menispermaceae) in subtropical China through chloroplast marker

Sinomenium acutum (Menispermaceae) is a traditional Chinese medicine. In recent years, extensive harvesting for medicinal purposes has resulted in a sharp decline in its population. Genetic information is crucial for the proper exploitation and conservation of Sinomenium acutum, but little is known about it at present. In this study, we analyzed 77 samples from 4 populations using four non-coding regions (atpI-atpH, trnQ-5rps16, trnH-psbA, and trnL-trnF) of chloroplast DNA and 14 haplotypes (from C1 to C14) were identified. C1 and C3 were common haplotypes, which were shared by all populations, and C3 was an ancestral haplotype, the rest were rare haplotypes. Obvious phylogeographic structure was not existed inferred by GST / NST test. Mismatch distribution, Tajimas D and Fus FS tests failed to support a rapid demographic expansion in Sinomenium acutum. AMOVA highlighted that the high level of genetic differentiation within population. Low genetic variation among populations illustrated gene flow was not restricted. Genetic diversity analyses demonstrated that the populations of Xuefeng, Dalou, and Daba Mountains were possible refugia localities of Sinomenium acutum. Based on this study, we proposed a preliminary protection strategy for it that C1, C3, C11 and C12 must be collected. These results offer an valuable and useful information for this species of population genetic study as well as further conservation.

molecular biology↗

bioRxiv2018

Fast, volumetric live-cell imaging using high-resolution light-field microscopy

Visualizing diverse anatomical and functional traits that span many spatial scales with high spatio-temporal resolution provides insights into the fundamentals of living organisms. Light-field microscopy (LFM) has recently emerged as a scanning-free, scalable method that allows for high-speed, volumetric functional brain imaging. Given those promising applications at the tissue level, at its other extreme, this highly-scalable approach holds great potential for observing structures and dynamics in single-cell specimens. However, the challenge remains for current LFM to achieve subcellular level, near-diffraction-limited 3D spatial resolution. Here, we report high-resolution LFM (HR-LFM) for live-cell imaging with a resolution of 300-700 nm in all three dimensions, an imaging depth of several micrometers, and a volume acquisition time of milliseconds. We demonstrate the technique by imaging various cellular dynamics and structures and tracking single particles. The method may advance LFM as a particularly useful tool for understanding biological systems at multiple spatio-temporal levels.

bioengineering↗

bioRxiv2018

Study on the Difference of Prokaryotic Flora Structure on the Surface of Micro-nano Coating with Different Antifouling Property

Low surface energy composite antifouling coatings prepared from carbon nanotubes (CNTs) and polydimethylsiloxane (PDMS) have good values for investigation of biofouling-related biological questions on marine biofilm. In order to deeply study the mechanism of antifouling on the surface of CNTs-PDMS coatings, it is necessary to investigate the structure of the microbial flora in the early biofilm on the coating surface. In the present study, the specific aim of this study was to investigate the structure differences of prokaryotic flora in biofilm samples at the early stage of biofouling through 16S rDNA based high-throughput DNA sequencing. By annotating high-throughput DNA sequencing results, this study identified dominant prokaryotic phyla and genera in biofilms of CNTs-PDMS coatings and identified significant differences in microbial composition and its dynamics among different coatings. Though the analysis of the Shannon index, Simpson index, Chao1 index and ACE index, coatings with better antifouling properties and antifouling properties have significant differences in community diversity and abundance, indicating different antifouling properties can affect the type and content of biofilm communities. According to the canonical correspondence analysis (CCA), time and temperature are more related to microbial community distribution, while the diameter and length of nanomaterials are less correlated. Through this study, the differences in microbial composition and content of prokaryotic communities, differences in diversity and abundance of sample communities, the differences between multiple samples and the correlation with important environmental factors were preliminarily analyzed, which laid a decent foundation for further research on the mechanism of anti-fouling on the surface of CNTs and PDMS coatings.

molecular biology↗

bioRxiv2018

Dystroglycan is a scaffold for extracellular axon guidance decisions

Axon guidance requires interactions between extracellular signaling molecules and transmembrane receptors, but how appropriate context-dependent decisions are coordinated outside the cell remains unclear. Here we show that the transmembrane glycoprotein Dystroglycan interacts with a changing set of environmental cues that regulate the trajectories of extending axons throughout the brain and spinal cord. Dystroglycan operates primarily as an extracellular scaffold during axon guidance, as it functions non-cell autonomously and does not require signaling through its intracellular domain. We identify the transmembrane receptor Celsr3/Adgrc3 as a binding partner for Dystroglycan, and show that this interaction is critical for specific axon guidance events in vivo. These findings establish Dystroglycan as a multifunctional scaffold that coordinates extracellular matrix proteins, secreted cues, and transmembrane receptors to regulate axon guidance.

neuroscience↗

bioRxiv2018

Knock-in rats expressing Cre and Flp recombinases at the Parvalbumin locus.

Rats have the ability to learn and perform sophisticated behavioral tasks, making them very useful for investigating neural circuit functions. In contrast to the extensive mouse genetic toolkit, the paucity of recombinase-expressing rat models has limited the ability to monitor and manipulate molecularly-defined neural populations in this species. Here we report the generation and validation of two knock-in rat strains expressing either Cre or Flp recombinase under the control of Parvalbumin (Pvalb), a gene expressed in the critical \"fast-spiking\" subset of inhibitory interneurons (FSIs). These strains were generated with CRISPR-Cas9 gene editing and show highly specific and penetrant labeling of Pvalb-expressing neurons, as demonstrated by in situ hybridization and immunohistochemistry. We validated these models in both prefrontal cortex and striatum using both ex vivo and in vivo approaches, including whole-cell recording, optogenetics, extracellular physiology and photometry. Our results demonstrate the utility of these new transgenic models for a wide range of neuroscience experiments.

neuroscience↗

bioRxiv2018

Impact of acetolactate synthase inactivation on 1,3-propanediol fermentation by Klebsiella pneumoniae

1,3-Propanediol (1,3-PDO) is an important compound that is mainly used in industry for polymer production. Fermentation of 1,3-PDO from glycerol by marine Klebsiella pneumoniae is accompanied by formation of 2,3-butanediol (2,3-BDO) as one of the main byproduct. The first step in the formation of 2,3-BDO from pyruvate is catalyzed by acetolactate synthase (ALS), an enzyme that competes with 1,3-PDO oxidoreductase for the cofactor NADH. This study aimed to analyze the impact of engineering the 2,3-BDO formation pathway via inactivation of ALS on 1,3-PDO fermentation by marine K. pneumoniae HSL4. An ALS mutant was generated using Red recombinase assisted gene replacement. The ALS specific activities of K. pneumoniae {Delta}ALS were notably lower than that of the wild-type strain. Fed-batch fermentation of the mutant strain resulted in a 1,3-PDO concentration, productivity and conversion of 72.04 g L-1, 2.25 g L-1 h-1, and 0.41 g g-1, a slightly increase compared with the parent strain. Moreover, inactivation of ALS decreased meso-2,3-BDO formation to trace amounts, significantly increased 2S,3S-BDO and lactate production, and a pronounced redistribution of intracellular metabolic flux was apparent.

microbiology↗

bioRxiv2018

CellTag Indexing: a genetic barcode-based multiplexing tool for single-cell technologies

Single-cell technologies have seen rapid advancements in recent years, along with new analytical challenges and opportunities. These high-throughput assays increasingly require special consideration in experimental design, sample multiplexing, batch effect removal, and data interpretation. Here, we describe a lentiviral barcode-based multiplexing approach, CellTag Indexing, where we transduce and label samples that can then be pooled together for downstream application and analysis. By introducing predefined genetic barcodes that are transcribed and readily detected, we can reliably read out sample identity via genomic or transcriptomic profiling, permitting the simultaneous assessment of cell grouping and transcriptional state. We validate and demonstrate the utility of CellTag Indexing by sequencing transcriptomes at single-cell resolution using a variety of cell types including mouse pre-B cells, primary mouse embryonic fibroblasts, human HEK293T cells, and mouse induced endoderm progenitors. Furthermore, we establish CellTag Indexing as a valuable tool for multiplexing direct lineage reprogramming perturbation experiments. We present CellTag Indexing as a broadly applicable genetic multiplexing tool that is complementary with existing single-cell RNA-sequencing and multiplexing strategies.

genomics↗

bioRxiv2018

PANDA: A comprehensive and flexible tool for proteomics data quantitative analysis

SummaryAs the experiment techniques and strategies in quantitative proteomics are improving rapidly, the corresponding algorithms and tools for protein quantification with high accuracy and precision are continuously required to be proposed. Here, we present a comprehensive and flexible tool named PANDA for proteomics data quantification. PANDA, which supports both label-free and labeled quantifications, is compatible with existing peptide identification tools and pipelines with considerable flexibility. Compared with MaxQuant on two complex da-tasets, PANDA was proved to be more accurate and precise with less computation time. Additionally, PANDA is an easy-to-use desktop ap-plication tool with user-friendly interfaces.\n\nAvailabilityPANDA is freely available for download at https://sourceforge.net/projects/panda-tools/.\n\nContact1987ccpacer@163.com and zhuyunping@gmail.com

bioinformatics↗

bioRxiv2018

A proteome-based design of bitter peptide digestion regime to attenuate cod-bone soup bitterness: comparison with a rainbow trout extract-mediated bitter taste masking approach

BACKGROUNDThe fresh bones (with some meat on them; frequently discarded as a large quantity of industry garbage) of marine fish such as cod and salmon are good materials for manufacture of food additives (taste adjusters). However, such fish-bone originated additives often have apparent bitter taste and need additional debittering regime.\n\nRESULTSIn this study, 46 known bitter peptides in the cod proteome were targeted for specific protease digestion to eliminate bitter taste from the cod bone soup. Though the debittering effect was apparent, the bitter taste was not completely removed. However, the bitter taste can be removed by addition of trout extract to a complete extent. The strong debittering power of rainbow trout extract was further confirmed by the debittering experiments on salmon bone soup and bitter melon, both with perfect results.\n\nCONCLUSIONThese results indicated that the cod bone soup bitterness comes not only from bitter peptide but also from other substances that can be masked by trout extract. Considering the fact that trout proteome has more potential bitter peptides than cod, trout extract shall have a strong bitter masking substance to be determined in the future.

biochemistry↗

bioRxiv2018

Thy1 transgenic mice expressing the red fluorescent calcium indicator jRGECO1a for neuronal population imaging in vivo

Calcium imaging is commonly used to measure the neural activity of large groups of neurons in mice. Genetically encoded calcium indicators (GECIs) can be delivered for this purpose using non-invasive genetic methods. Compared to viral gene transfer, transgenic targeting of GECIs provides stable long-term expression and obviates the need for invasive viral injections. Transgenic mice expressing the green GECI GCaMP6 are already widely used. Here we present the generation and characterizarion of transgenic mice expressing the sensitive red GECI jRGECO1a, driven by the Thy1 promoter. Four transgenic lines with different expression patterns showed sufficiently high expression for cellular in vivo imaging. We used two-photon microscopy to characterize visual responses of individual neurons in the visual cortex in vivo. The signal-to-noise ratio in transgenic mice was comparable to, or better than, for mice transduced with adeno-associated virus. We also show that Thy1-jRGECO1a transgenic mice are useful for transcranial population imaging and functional mapping using widefield fluorescecnce microscopy. We also demonstrate imaging of visual responses in retinal ganglion cells. Thy1-jRGECO1a transgenic mice are therefore a useful addition to the toolbox for imaging activity in intact neural networks.

neuroscience↗

bioRxiv2017

Transcriptome dynamics describe and predict state transition from health to leukemia

Temporal dynamics of gene expression are informative of changes associated with disease development and evolution. Given the complexity of high-dimensional temporal datasets, an analytical framework guided by a robust theory is needed to interpret time-sequential changes and to predict system dynamics. Herein, we use acute myeloid leukemia as a proof-of-principle to model gene expression dynamics in a transcriptome state-space constructed based on time-sequential RNA-sequencing data. We describe the construction of a state-transition model to identify state-transition critical points which accurately predicts leukemia development. We show an analytical approach based on state-transition critical points identified step-wise transcriptomic perturbations driving leukemia progression. Furthermore, the gene(s) trajectory and geometry of the transcriptome state-space provides biologically-relevant gene expression signals that are not synchronized in time, and allows quantification of gene(s) contribution to leukemia development. Therefore, our state-transition model can synthesize information, identify critical points to guide interpretation of transcriptome trajectories and predict disease development.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=193 HEIGHT=200 SRC=\"FIGDIR/small/238923v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (55K):\norg.highwire.dtl.DTLVardef@12eeaccorg.highwire.dtl.DTLVardef@1392af9org.highwire.dtl.DTLVardef@34786dorg.highwire.dtl.DTLVardef@ce78bb_HPS_FORMAT_FIGEXP M_FIG C_FIG In briefThe theory of state-transition is applied to acute myeloid leukemia (AML) to model transcriptome dynamics and trajectories in a state-space, and is used to identify critical points corresponding to critical transcriptomic perturbations that predict leukemia development.\n\nHighlightsO_LILeukemia transcriptome dynamics are modeled as movement in transcriptome state-space\nC_LIO_LIState-transition model and critical points accurately predicts leukemia development\nC_LIO_LICritical point-based approach identifies step-wise transcriptome events in leukemia\nC_LIO_LIState-based geometric analysis provides quantification of leukemogenic contribution\nC_LI

cancer biology↗