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Si Wu

Publications and source records attributed to Si Wu.

6 recordsLinked to original sources
PubMed2025

The homeostasis of β-alanine is key for Arabidopsis reproductive growth and development.

β-Alanine, an abundant non-proteinogenic amino acid, acts as a precursor for coenzyme A and plays a role in various stress responses. However, a comprehensive understanding of its metabolism in plants remains incomplete. Previous metabolic genome-wide association studies (mGWAS) identified ALANINE:GLYOXYLATE AMINOTRANSFERASE2 (AGT2, AT4G39660) linked to β-alanine levels in Arabidopsis under normal conditions. In this study, we aimed to deepen our insights into β-alanine regulation by conducting mGWAS under two contrasting environmental conditions: control (12 h photoperiod, 21°C, 150 μmol m-2 sec-1) and stress (harvested after 1820 min at 32°C and darkness). We identified two highly significant quantitative trait loci (QTL) for β-alanine, including the AGT2 locus associated in both environments and ALDEHYDE DEHYDROGENASE6B2 (ALDH6B2, AT2G14170) associated only under stress conditions. A coexpression-correlation network revealed that the regulatory pathway involving β-alanine levels, AGT2, and ALDH6B2 connects the branched chained amino acid (BCAA) degradation through the propionate pathway. Metabolic profiles of AGT2 overexpression (OE) and knock-out (KO) lines (agt2) across various organs and developmental stages established the critical role of AGT2 in β-alanine metabolism. This work underscores the importance of β-alanine homeostasis for proper growth and development in Arabidopsis.

Arabidopsis↗
PubMed2003

Polymerization of calsequestrin. Implications for Ca2+ regulation.

Two distinct dimerization contacts in calsequestrin crystals suggested a mechanism for Ca(2+) regulation resulting from the occurrence of coupled Ca(2+) binding and protein polymerization. Ca(2+)-induced formation of one contact was proposed to lead to dimerization followed by Ca(2+)-induced formation of the second contact to bring about polymerization (). To test this mechanism, we compared canine cardiac calsequestrin and four truncation mutants with regard to their folding properties, structures, and Ca(2+)-induced polymerization. The wild-type calsequestrin and truncation mutants exhibited similar K(+)-induced folding and end-point structures as indicated by intrinsic fluorescence and circular dichroism, respectively, whereas the polymerization tendencies of the wild-type calsequestrin differed markedly from the polymerization tendencies of the truncation mutants. Static laser light scattering and 3,3'-dithiobis sulfosuccinimidyl-propionate cross-linking indicated that wild-type protein exhibited an initial Ca(2+)-induced dimerization, followed by additional oligomerization as the Ca(2+) concentration was raised or as the K(+) concentration was lowered. None of the truncation mutants exhibited clear stepwise oligomerization that depended on increasing Ca(2+) concentration. Comparison of the three-dimensional structure of rabbit skeletal calsequestrin with a homology model of canine cardiac calsequestrin from the point of view of our coupled Ca(2+) binding and polymerization mechanism leads to a possible explanation for the 2-fold reduced Ca(2+) binding capacity of cardiac calsequestrin despite very similar overall net negative charge for the two proteins.

Amino Acid Sequence↗
PubMed2003

Synchronous firing and higher-order interactions in neuron pool.

The stochastic mechanism of synchronous firing in a population of neurons is studied from the point of view of information geometry. Higher-order interactions of neurons, which cannot be reduced to pairwise correlations, are proved to exist in synchronous firing. In a neuron pool where each neuron fires stochastically, the probability distribution q(r) of the activity r, which is the fraction of firing neurons in the pool, is studied. When q(r) has a widespread distribution, in particular, when q(r) has two peaks, the neurons fire synchronously at one time and are quiescent at other times. The mechanism of generating such a probability distribution is interesting because the activity r is concentrated on its mean value when each neuron fires independently, because of the law of large numbers. Even when pairwise interactions, or third-order interactions, exist, the concentration is not resolved. This shows that higher-order interactions are necessary to generate widespread activity distributions. We analyze a simple model in which neurons receive common overlapping inputs and prove that such a model can have a widespread distribution of activity, generating higher-order stochastic interactions.

Neurons↗
PubMed2003

Sequential Bayesian decoding with a population of neurons.

Population coding is a simplified model of distributed information processing in the brain. This study investigates the performance and implementation of a sequential Bayesian decoding (SBD) paradigm in the framework of population coding. In the first step of decoding, when no prior knowledge is available, maximum likelihood inference is used; the result forms the prior knowledge of stimulus for the second step of decoding. Estimates are propagated sequentially to apply maximum a posteriori (MAP) decoding in which prior knowledge for any step is taken from estimates from the previous step. Not only do we analyze the performance of SBD, obtaining the optimal form of prior knowledge that achieves the best estimation result, but we also investigate its possible biological realization, in the sense that all operations are performed by the dynamics of a recurrent network. In order to achieve MAP, a crucial point is to identify a mechanism that propagates prior knowledge. We find that this could be achieved by short-term adaptation of network weights according to the Hebbian learning rule. Simulation results on both constant and time-varying stimulus support the analysis.

Bayes Theorem↗
PubMed2002

Characterization of human RNA polymerase III identifies orthologues for Saccharomyces cerevisiae RNA polymerase III subunits.

Unlike Saccharomyces cerevisiae RNA polymerase III, human RNA polymerase III has not been entirely characterized. Orthologues of the yeast RNA polymerase III subunits C128 and C37 remain unidentified, and for many of the other subunits, the available information is limited to database sequences with various degrees of similarity to the yeast subunits. We have purified an RNA polymerase III complex and identified its components. We found that two RNA polymerase III subunits, referred to as RPC8 and RPC9, displayed sequence similarity to the RNA polymerase II RPB7 and RPB4 subunits, respectively. RPC8 and RPC9 associated with each other, paralleling the association of the RNA polymerase II subunits, and were thus paralogues of RPB7 and RPB4. Furthermore, the complex contained a prominent 80-kDa polypeptide, which we called RPC5 and which corresponded to the human orthologue of the yeast C37 subunit despite limited sequence similarity. RPC5 associated with RPC53, the human orthologue of S. cerevisiae C53, paralleling the association of the S. cerevisiae C37 and C53 subunits, and was required for transcription from the type 2 VAI and type 3 human U6 promoters. Our results provide a characterization of human RNA polymerase III and show that the RPC5 subunit is essential for transcription.

Amino Acid Sequence↗
PubMed2002

Population coding and decoding in a neural field: a computational study.

This study uses a neural field model to investigate computational aspects of population coding and decoding when the stimulus is a single variable. A general prototype model for the encoding process is proposed, in which neural responses are correlated, with strength specified by a gaussian function of their difference in preferred stimuli. Based on the model, we study the effect of correlation on the Fisher information, compare the performances of three decoding methods that differ in the amount of encoding information being used, and investigate the implementation of the three methods by using a recurrent network. This study not only rediscovers main results in existing literatures in a unified way, but also reveals important new features, especially when the neural correlation is strong. As the neural correlation of firing becomes larger, the Fisher information decreases drastically. We confirm that as the width of correlation increases, the Fisher information saturates and no longer increases in proportion to the number of neurons. However, we prove that as the width increases further--wider than (sqrt)2 times the effective width of the turning function--the Fisher information increases again, and it increases without limit in proportion to the number of neurons. Furthermore, we clarify the asymptotic efficiency of the maximum likelihood inference (MLI) type of decoding methods for correlated neural signals. It shows that when the correlation covers a nonlocal range of population (excepting the uniform correlation and when the noise is extremely small), the MLI type of method, whose decoding error satisfies the Cauchy-type distribution, is not asymptotically efficient. This implies that the variance is no longer adequate to measure decoding accuracy.

Neural Networks, Computer↗