Biology subjects

Tu, Y.

Publications and source records attributed to Tu, Y..

43 records · Page 3Linked to original sources

bioRxiv2020

Genome-wide association study of flowering time reveals complex genetic heterogeneity and epistatic interactions in rice

Since domestication, rice has cultivated in a wide range of latitudes with different day lengths. Selection of diverse natural variations in heading date and photoperiod sensitivity is critical for adaptation of rice to different geographical environments. To unravel the genetic architecture underlying natural variation of rice flowering time, we conducted a genome wide association study (GWAS) using several association analysis strategies with a diverse worldwide collection of 529 O. sativa accessions. Heading date was investigated in three environments under long-day or short-day conditions, and photosensitivity was evaluated. By dividing the whole association panel into subpopulations and performing GWAS with both linear mixed models and multi-locus mixed-models, we revealed hundreds of significant loci harboring novel candidate genes as well as most of the known flowering time genes. In total, 127 hotspots were detected in at least two GWAS. Universal genetic heterogeneity was found across subpopulations. We further detected abundant interactions between GWAS loci, especially in indica. Functional gene families were revealed from enrichment analysis of the 127 hotspots. The results demonstrated a rich of genetic interactions in rice flowering time genes and such epistatic interactions contributed to the large portions of missing heritability in GWAS. It suggests the increased complexity of genetic heterogeneity might discount the power of increasing the sample sizes in GWAS.

genetics↗

bioRxiv2020

A filter-and-integrate mechanism generates stochastictranscriptional pulses in E.coli flagellar synthesis

Stochastic pulsatile dynamics have been observed in an increasing number of biological circuits with typical mechanism involving feedback control. Surprisingly, recent single-cell experiments showed that E. coli flagellar class-2&3 promoters are activated in stochastic pulses without the means of feedback, however, the underlying design principles of pulse generation have remained unclear. Here, by developing a system-level stochastic model constrained by a large set of E. coli flagellar synthesis data from different strains and mutants, we identify the underlying design principles for generating stochastic transcriptional pulses without feedback. Our model shows that YdiV, an inhibitor of the class-1 master regulator (FlhDC), creates an ultrasensitve switch that serves as a digital filter to eliminate small amplitude FlhDC fluctuations. Additionally, we demonstrate that fast temporal fluctuations of FlhDC are smoothed out and integrated over time before affecting class-2 downstream genes. Together, our results reveal the existence of a filter-and-integrate design that is necessary for generating stochastic pulses without feedback. This strategy suggests that E. coli may avoid premature activation of the expensive flagellar gene expression by filtering input fluctuations in intensity and in time.

microbiology↗

bioRxiv2019

Error-speed correlations in biopolymer synthesis

Synthesis of biopolymers such as DNA, RNA, and proteins are biophysical processes aided by enzymes. Performance of these enzymes is usually characterized in terms of their average error rate and speed. However, because of thermal fluctuations in these single-molecule processes, both error and speed are inherently stochastic quantities. In this paper, we study fluctuations of error and speed in biopolymer synthesis and show that they are in general correlated. This means that, under equal conditions, polymers that are synthesized faster due to a fluctuation tend to have either better or worse errors than the average. The error-correction mechanism implemented by the enzyme determines which of the two cases holds. For example, discrimination in the forward reaction rates tends to grant smaller errors to polymers with faster synthesis. The opposite occurs for discrimination in monomer rejection rates. Our results provide an experimentally feasible way to identify error-correction mechanisms by measuring the error-speed correlations.

biophysics↗

bioRxiv2018

Statistical properties of the optimal sensitivity matrix for compressed sensing with nonlinear sensors

There are numerous different odorant molecules in nature. Typical odors are sparse mixtures of a few types of odorant molecules each with a wide range of concentrations. However, there are only a relatively small number of olfactory receptor neurons (ORNs), which respond to odorant concentration nonlinearly (sigmoidal) with a finite sensitivity range. Thus, how to encode a large number of sparse odor mixtures with a relatively small number of nonlinear ORNs - the nonlinear compressed sensing problem - remains a puzzle. Here, by using an information theory approach, we study the optimal coding strategies that enable nonlinear ORNs to best represent olfactory information (both the odorants identities and their concentrations) in sparse odor mixtures. Our extensive numerical simulations and analytical analysis show that the optimal odor-receptor sensitivity matrix is sparse and the nonzero sensitivities follow roughly a log-normal distribution(matching the statistics of the odorants), both of which are consistent with existing experiments. For ORNs with a finite basal activity, our study shows that co-existence of both odor-evoked excitation and inhibition increases coding capacity, which provides a plausible explanation for such co-existence observed in the fly olfactory system. Furthermore, we show that coding the inputs with the optimal sensitivity matrix can enhance accuracy of the downstream decoding and learning tasks. These general statistical properties of the optimal sensitivity matrix for nonlinear compressed sensing may shed light on understanding the peripheral olfactory sensory system and improving performance of artificial neural networks.

neuroscience↗

bioRxiv2018

PRL-1 is required for neuroprotection against olfactory CO2 stimulation in Drosophila

The Mammalian phosphatase of regenerating liver (PRL) family is primarily recognized for its oncogenic properties. Here we found that in Drosophila, loss of prl-1 resulted in CO2-induced brain disorder presented as irreversible wing hold up with enhancement of Ca2+ responses at the neuron synaptic terminals. Overexpression of Prl-1 in the nervous system could rescue the mutant phenotype. We show that Prl-1 is particularly expressed in CO2-responsive neural circuit and the higher brain centers. Ablation of the CO2 olfactory receptor, Gr21a, suppressed the mutant phenotype, suggesting that CO2 acts as a neuropathological substrate in absence of Prl-1. Further studies found that the wing hold up is an obvious consequence upon knockdown of Uex, a magnesium transporter, which directly interacts with Prl-1. Conditional expression of Uex in the nervous system could rescue the phenotype of prl-1 mutants. We demonstrate that Uex acts genetically downstream of Prl-1. Our findings provide important insights into mechanisms of Prl-1 protection against olfactory CO2 stimulation induced brain disorder at the level of detailed neural circuits and functional molecular connections.

neuroscience↗

bioRxiv2018

Activity of Antimicrobial Peptides Decreases with Increased Cell Membrane Crossing Free Energy Cost

Antimicrobial peptides (AMPs) are a promising alternative to mitigating bacterial infections in light of increasing bacterial resistance to antibiotics. However, predicting, understanding, and controlling the antibacterial activity of AMPs remains a significant challenge. While peptide intramolecular interactions are known to modulate AMP antimi-crobial activity, peptide intermolecular interactions remain elusive in their impact on peptide bioactivity. Herein, we test the relationship between AMP intermolecular interactions and antibacterial efficacy by controlling AMP intermolecular hydrophobic and hydrogen bonding interactions. Molecular dynamics simulations and Gibbs free energy calculations in concert with experimental assays show that increasing intermolecular interactions via inter-peptide aggregation increases the energy cost for the peptide to cross the bacterial cell membrane, which in turn decreases the AMP antibacterial activity. Our findings provide a route for predicting and controlling the antibacterial activity of AMPs against Gramnegative bacteria via reductions of intermolecular AMP interactions.

biophysics↗

bioRxiv2017

Deciphering the regulation mechanism in biochemical networks by a systems-biology approach

To decipher molecular mechanisms in biological systems from system-level input-output data is challenging especially for complex processes that involve interactions among multiple components. Here, we study regulation of the multi-domain (P1-5) histidine kinase CheA by the MCP chemoreceptors. We develop a network model to describe dynamics of the system treating the receptor complex with CheW and P3P4P5 domains of CheA as a regulated enzyme with two substrates, P1 and ATP. The model enables us to search the hypothesis space systematically for the simplest possible regulation mechanism consistent with the available data. Our analysis reveals a novel dual regulation mechanism wherein besides regulating ATP binding the receptor activity has to regulate one other key reaction, either P1 binding or phosphotransfer between P1 and ATP. Furthermore, our study shows that the receptors only control kinetic rates of the enzyme without changing its equilibrium properties. Predictions are made for future experiments to distinguish the remaining two dual-regulation mechanisms. This systems-biology approach of combining modeling and a large input-output data-set should be applicable for studying other complex biological processes.

systems biology↗