Biology subjects

You, L.

Publications and source records attributed to You, L..

66 records · Page 4Linked to original sources

bioRxiv2019

Arabidopsis PPC2 is crucial for growth at low CO2 by involvement in photorespiratory metabolism and integration of ABI5

Phosphoenolpyruvate carboxylase (PEPC) is a pivotal enzyme that plays a key role in photosynthetic CO2 fixation in C4. However, the function of C3 PEPCs and their roles at environmental CO2 changes are still limited. Here, we report the role of PPC2 in seedling growth at low CO2 by linking photorespiratory metabolism with primary metabolism and involvement of ABA and ABI5. Mutation of PPC2 caused seedling growth arrest, with reduced Fv/Fm, photosynthetic carbohydrates and ABA biosynthesis at low CO2. PPC2 is induced by low CO2 and the PEPC activity was greatly reduced in ppc2 leaves. Moreover, metabolic analyses showed the photorespiratory intermediates, glycine and serine, were greatly increased and primary metabolites were reduced. Application of sucrose, malate and ABA greatly rescued the growth arrest phenotype of ppc2. The expression of glycine/serine synthesis and metabolism related photorespiratory enzyme genes were decreased in ppc2 and regulated by ABI5 at low CO2 conditions. ppc2 and abi5 mature plants exhibited reduced A-Ci curves at relatively low CO2, which could be recovered by non-photorespiratory low oxygen conditions. ABI5 expression greatly rescued the growth arrest and A-Ci curves of ppc2 at low CO2. Our findings demonstrate the important role of C3 PEPCs in carbon fixation and metabolism.

plant biology↗

bioRxiv2019

Crl activates transcription by stabilizing the active conformation of the master stress factor σS

{sigma}S is a master transcription initiation factor that protects bacterial cells from various harmful environmental stresses and antibiotic pressure. Although its mechanism remains unclear, it is known that full activation of {sigma}S-mediated transcription requires a {sigma}S-specific activator, Crl. In this study, we determined a 3.80 [A] cryo-EM structure of an E. coli transcription activation complex (E. coli Crl-TAC) comprising E. coli {sigma}S-RNAP holoenzyme, Crl, and a nucleic-acid scaffold. The structure reveals that Crl interacts with the domain 2 of {sigma}S ({sigma}S2), sharing no interaction with promoter DNA. Subsequent hydrogen-deuterium exchange mass spectrometry (HDX-MS) results indicate that Crl stabilizes key structural motifs of {sigma}S2 to promote the assembly of {sigma}S-RNAP holoenzyme and also to facilitate formation of the RNA polymerase-promoter DNA open complex (RPo). Our study demonstrates a unique DNA contact-independent mechanism of transcription activation, thereby defining a previously unrecognized mode of transcription activation in cells.

biochemistry↗

bioRxiv2019

Quantifying E2F1 protein dynamics in single cells

The Rb/E2F pathway plays a central role in regulating cell-fate decisions and cell-cycle progression. The E2F1 protein, a major effector of the pathway, is regulated via a combination of transcriptional, translational and posttranslational constraints. Elucidating the regulation and impact of the Rb/E2F pathway requires direct measurement of E2F1 dynamics in single cells. To this end, we have engineered fluorescent E2F1 protein reporters to enable live detection and quantification in single cells. The reporter constructs expressed an E2F1-Venus fusion protein under the regulation of the mouse or human E2F1 promoter and contained or excluded the 3UTR of the E2F1 gene, a sequence that contains miRNA regulatory regions that modulate expression of the protein. Expression of the reporter protein was highly dynamic during the cell cycle: there was no or little fluorescent signal in G0, but levels steadily increased during late G1 and peaked during mid to late S phase before returning to baseline before the onset of mitosis. The absence of the E2F1 3UTR in the constructs led to considerably higher steady-state levels of the fusion protein, which although normally regulated, exhibited a slightly less complex dynamic profile during the cell cycle or genotoxic stress. Lastly, the presence or absence of Rb failed to impact in substantial ways the overall detection and levels of the reporters.

cell biology↗

bioRxiv2019

High-throughput isolation and culture of human gut bacteria with droplet microfluidics

Isolation and culture of gut bacteria enable testing for microbial roles in disease and may also lead to novel therapeutics. However, the diversity of human gut microbial communities (microbiota) impedes comprehensive experimental studies of individual bacterial taxa. Here, we combine advances in droplet microfluidics and high-throughput DNA sequencing to develop a platform for isolating and assaying microbiota members in picoliter droplets (MicDrop). MicDrop can be used to create millions of distinct bacterial colonies in a single experiment while using off-the-shelf parts compact enough to fit in an anaerobic chamber. In proof-of-concept experiments, we used the platform to characterize inter-individual metabolic variation among hundreds of polysaccharide-degrading gut bacteria from nine stool donors. We also used MicDrop to test the hypothesis that growth kinetics of individual gut bacterial taxa are associated with longterm community dynamics in an artificial gut. These demonstrations suggest the MicDrop platform could support future diagnostic efforts to personalize microbiota-directed therapies, as well as to provide comprehensive new insights into the ecology of human gut microbiota.

microbiology↗

bioRxiv2019

Massive computational acceleration by using neural networks to emulate mechanism-based biological models

Mechanism-based mathematical models are the foundation for diverse applications. It is often critical to explore the massive parametric space for each model. However, for many applications, such as agent-based models, partial differential equations, and stochastic differential equations, this practice can impose a prohibitive computational demand. To overcome this limitation, we present a fundamentally new framework to improve computational efficiency by orders of magnitude. The key concept is to train an artificial neural network using a limited number of simulations generated by a mechanistic model. This number is small enough such that the simulations can be completed in a short time frame but large enough to enable reliable training of the neural network. The trained neural network can then be used to explore the system dynamics of a much larger parametric space. We demonstrate this notion by training neural networks to predict self-organized pattern formation and stochastic gene expression. With this framework, we can predict not only the 1-D distribution in space (for partial differential equation models) and probability density function (for stochastic differential equation models) of variables of interest with high accuracy, but also novel system dynamics not present in the training sets. We further demonstrate that using an ensemble of neural networks enables the self-contained evaluation of the quality of each prediction. Our work can potentially be a platform for faster parametric space screening of biological models with user defined objectives.

systems biology↗

bioRxiv2019

Genome-wide identification and analysis of A-to-I RNA editing events in the malignantly transformed cell lines from BEP2D induced by α-particles radiation

Adenosine (A) to inosine (I) RNA editing is the most prevalent RNA editing mechanism in humans and play critical roles in tumorigenesis. However, the effects of radiation on RNA editing and the mechanisms of radiation-induced cancer were poorly understood. Here, we analyzed human bronchial epithelial BEP2D cells and radiation-induced malignantly transformed cells with next generation sequencing. By performing an integrated analysis of A-to-I RNA editing, we found that genome-encoded single-nucleotide polymorphisms (SNPs) might induce the downregulation of ADAR2 enzymes, and further caused the abnormal occurrence of RNA editing in malignantly transformed cells. These editing events were significantly enriched in differentially expressed genes between normal cells and cancer cells. In addition, oncogenes CTNNB1 and FN1 were highly edited and significantly overexpressed in cancer cells, thus may be responsible for the lung cancer progression. Our work provides a systematic analysis of RNA editing from lung tumor specimens with high-throughput RNA sequencing and DNA sequencing. Moreover, these results demonstrate further evidence for RNA editing as an important tumorigenesis mechanism.

genetics↗

bioRxiv2018

Towards multi-drug adaptive therapy

A new ecologically inspired paradigm in cancer treatment known as \"adaptive therapy\" capitalizes on competitive interactions between drug-sensitive and drug-resistant subclones. The goal of adaptive therapy is to maintain a controllable stable tumor burden by allowing a significant population of treatment sensitive cells to survive. These, in turn, suppress proliferation of the less fit resistant populations. However, there remain several open challenges in designing adaptive therapies, particularly in extending these therapeutic concepts to multiple treatments. We present a cancer treatment case study (metastatic castrate resistant prostate cancer) as a point of departure to illustrate three novel concepts to aid the design of multi-drug adaptive therapies. First, frequency-dependent \"cycles\" of tumor evolution can trap tumor evolution in a periodic, controllable loop. Second, the availability and selection of treatments may limit the evolutionary \"absorbing region\" reachable by the tumor. Third, the velocity of evolution significantly influences the optimal timing of drug sequences.

cancer biology↗

bioRxiv2018

Effects of Biogas Slurry on Fruit Economic Traits and Soil Nutrient of Camellia oleifera Abel

Soil nutrients play a principal role in Camellia oleifera Abel (oil-seed camellia) production. Camellia oleifera absorbs nutrients from surrounding soils and its production is highly influenced by nutrients or fertilization. In this study, we investigated the effects of biogas slurry applications on soil nutrients and economic traits of C. oleifera fruits. Five different amounts of fertilizing biogas slurry (0, 10, 20, 30, or 40 kg/plant/year from three applications per year) were applied to C. oleifera plants in 2015 and 2016. Rhizosphere soil nutrients and C. oleifera fruit economic traits (yield, seed rate, and oil yield)were measured. Fertilization with biogas slurryincreasedsoil organic matter, available nitrogen (N), phosphorus (P), and potassium (K) in both 2015 and 2016. Increases in soil available N, P, and Kwere largest at the highest slurry application rate and second largest at the second highest application rate. Fruit economic traits were maximized at the two highest application rates. Oil yield was correlated withsoil available P in 2015 and 2016, and soil organic matter in 2015. Fertilization with biogas slurry decreased saturated fatty acid content in fruit but had no effect on unsaturated fatty acid content. In conclusion, fertilization with biogas slurry increases rhizosphere soil nutrients and fruit economic traits of C. oleifera with the rates of at least 30 kg/plant/year having the most positive effects.

plant biology↗

bioRxiv2018

Heterogeneous timing of asexual cycles in Plasmodium falciparum quantified by extended time-lapse microscopy

Malarial fever arises from the synchronous bursting of human red blood cells by the Plasmodium parasite. The released parasites re-infect neighboring red blood cells and undergo another asexual cycle of differentiation and proliferation for 48 hours, before again bursting synchronously. The synchrony of bursting is lost during in vitro culturing of the parasite outside the human body, presumably because the asexual cycle is no longer entrained by host-specific circadian cues. Therefore, most in vitro malaria studies have relied on the artificial synchronization of the parasite population. However, much remains unknown about the degree of timing heterogeneity of asexual cycles and how artificial synchronization may affect this timing. Here, we combined time-lapse fluorescence microscopy and long-term culturing to follow single cells and directly measure the heterogeneous timing of in vitro asexual cycles. We first demonstrate that unsynchronized laboratory cultures are not fully asynchronous and the parasites exhibit a bimodal distribution in their first burst times. We then show that synchronized and unsynchronized cultures had similar asexual cycle periods, which indicates that artificial synchronization does not fundamentally perturb asexual cycle dynamics. Last, we demonstrate that sibling parasites descended from the same schizont exhibited significant variation in asexual cycle period, although smaller than the variation between non-siblings. The additional variance between non-siblings likely arises from the variable environments and/or developmental programs experienced in different host cells.

microbiology↗

bioRxiv2018

Unifying mutualism diversity for interpretation and prediction

Coarse-grained rules are widely used in chemistry, physics and engineering. In biology, however, such rules are less common and under-appreciated. This gap can be attributed to the difficulty in establishing general rules to encompass the immense diversity and complexity of biological systems. Even when a rule is established, it is often challenging to map it to mechanistic details and to quantify these details. We here address these challenges on a study of mutualism, an essential type of ecological interaction in nature. Using an appropriate level of abstraction, we deduced a general rule that predicts the outcomes of mutualistic systems, including coexistence and productivity. We further developed a standardized calibration procedure to apply the rule to mutualistic systems without the need to fully elucidate or characterize their mechanistic underpinnings. Our approach consistently provides explanatory and predictive power with various simulated and experimental mutualistic systems. Our strategy can pave the way for establishing and implementing other simple rules for biological systems.

systems biology↗

bioRxiv2018

Dissecting bacterial resistance and resilience in antibiotic responses

An essential property of microbial communities is the ability to survive a disturbance. Survival can be achieved through resistance, the ability to absorb effects of a disturbance without a significant change, or resilience, the ability to recover after being perturbed by a disturbance. These concepts have long been applied to the analysis of ecological systems, though their interpretations are often subject to debate. Here we show that this framework readily lends itself to the dissection of the bacterial response to antibiotic treatment, where both terms can be unambiguously defined. The ability to tolerate the antibiotic treatment in the short term corresponds to resistance, which primarily depends on traits associated with individual cells. In contrast, the ability to recover after being perturbed by an antibiotic corresponds to resilience, which primarily depends on traits associated with the population. This framework effectively reveals the phenotypic signatures of bacterial pathogens expressing extended spectrum {beta}-lactamases (ESBLs), when treated by a {beta}-lactam antibiotic. Our analysis has implications for optimizing treatment of these pathogens using a combination of a {beta}-lactam and a {beta}-lactamase (Bla) inhibitor. In particular, our results underscore the need to dynamically optimize combination treatments based on the quantitative features of the bacterial response to the antibiotic or the Bla inhibitor.

cell biology↗

bioRxiv2017

DNA 5-Hydroxymethylcytosines from Cell-free Circulating DNA as Diagnostic Biomarkers for Human Cancers

DNA modifications such as 5-methylcytosines (5mC) and 5-hydroxymethylcytosines (5hmC) are epigenetic marks known to affect global gene expression in mammals(1, 2). Given their prevalence in the human genome, close correlation with gene expression, and high chemical stability, these DNA epigenetic marks could serve as ideal biomarkers for cancer diagnosis. Taking advantage of a highly sensitive and selective chemical labeling technology(3), we report here genome-wide 5hmC profiling in circulating cell-free DNA (cfDNA) and in genomic DNA of paired tumor/adjacent tissues collected from a cohort of 90 healthy individuals and 260 patients recently diagnosed with colorectal, gastric, pancreatic, liver, or thyroid cancer. 5hmC was mainly distributed in transcriptionally active regions coincident with open chromatin and permissive histone modifications. Robust cancer-associated 5hmC signatures in cfDNA were identified with specificity for different cancers. 5hmC-based biomarkers of circulating cfDNA demonstrated highly accurate predictive value for patients with colorectal and gastric cancers versus healthy controls, superior to conventional biomarkers, and comparable to 5hmC biomarkers from tissue biopsies. This new strategy could lead to the development of effective blood-based, minimally-invasive cancer diagnosis and prognosis approaches.

cancer biology↗