Single-molecule modeling of mRNA degradation by miRNA: Lessons from data

Recent experimental results on the effect of miRNA on the decay of its target mRNA have been analyzed against a previously hypothesized single molecule degradation pathway. According to that hypothesis, the silencing complex (miRISC) first interacts with its target mRNA and then recruits the protein complexes associated with NOT1 and PAN3 to trigger deadenylation (and subsequent degradation) of the target mRNA. Our analysis of the experimental decay patterns allowed us to refine the structure of the degradation pathways at the single molecule level. Surprisingly, we found that if the previously hypothesized network was correct, only about 7% of the target mRNA would be regulated by the miRNA mechanism, which is inconsistent with the available knowledge. Based on systematic data analysis, we propose the alternative hypothesis that NOT1 interacts with miRISC before binding to the target mRNA. Moreover, we show that when miRISC binds alone to the target mRNA, the mRNA is degraded more slowly, probably through a deadenylation-independent pathway. The new biochemical pathway we propose both fits the data and paves the way for new experimental work to identify new interactions.Comment: It contains also the Supplementary Materials as appendix

Kinetic analysis of protein stability reveals age-dependent degradation

Do young and old protein molecules have the same probability to be degraded? We addressed this question using metabolic pulse-chase labeling and quantitative mass spectrometry to obtain degradation profiles for thousands of proteins. We find that gt;10 of proteins are degraded non-exponentially. Specifically, proteins are less stable in the first few hours of their life and stabilize with age. Degradation profiles are conserved and similar in two cell types. Many non-exponentially degraded (NED) proteins are subunits of complexes that are produced in super-stoichiometric amounts relative to their exponentially degraded (ED) counterparts. Within complexes, \NED\} proteins have larger interaction interfaces and assemble earlier than \{ED\} subunits. Amplifying genes encoding \{NED\ proteins increases their initial degradation. Consistently, decay profiles can predict protein level attenuation in aneuploid cells. Together, our data show that non-exponential degradation is common, conserved, and has important consequences for complex formation and regulation of protein abundance

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Algorithmic Parameter Space Reduction of a Systems Biology Model: A Case Study

Ordinary differential equation (ODE) models are often used to quantitatively describe and predict the dynamic responses of biological and other systems. Models with many parameters, limited measurement data and in need of quantification are typically unidentifiable from available input/output data. Even models that are structurally identifiable can be difficult to quantify in practice from limited data. For overparameterized models (OPMs), it is often helpful to simplify the model, by rationally reducing the dimensionality of the parameter space. This is done by finding a set of "key parameters" to estimate, a subset that best represents the dominant model dynamic responses. OPMs are often characterized by pairwise parameter correlations close to 1 in magnitude and at least some unacceptably large parameter estimation variances. The goal is to get the best fit possible with a smaller number of parameters, each with acceptable variances. Several published methods for selecting the key parameter subset are based on parameter sensitivity analysis and/or analysis of the parameter covariance matrix estimated from the input/output data. We apply a combination of these methods to an overparameterized candidate model of tumor suppressor protein p53. The model comprises of 4 ODEs, 23 unknown parameters, and noisy output measurements of the 4 state variables and the input. Three least sensitive and highly correlated parameters were isolated from the analysis and fixed to nominal values. This reduced the parameter search space and yielded substantially improved numerical identifiability properties for the resulting simplified model which fitted the data equally well, using both global and local search algorithms

Algorithmic Parameter Space Reduction of a Systems Biology Model: A Case Study

Ordinary differential equation (ODE) models are often used to quantitatively describe and predict the dynamic responses of biological and other systems. Models with many parameters, limited measurement data and in need of quantification are typically unidentifiable from available input/output data. Even models that are structurally identifiable can be difficult to quantify in practice from limited data. For overparameterized models (OPMs), it is often helpful to simplify the model, by rationally reducing the dimensionality of the parameter space. This is done by finding a set of "key parameters" to estimate, a subset that best represents the dominant model dynamic responses. OPMs are often characterized by pairwise parameter correlations close to 1 in magnitude and at least some unacceptably large parameter estimation variances. The goal is to get the best fit possible with a smaller number of parameters, each with acceptable variances. Several published methods for selecting the key parameter subset are based on parameter sensitivity analysis and/or analysis of the parameter covariance matrix estimated from the input/output data. We apply a combination of these methods to an overparameterized candidate model of tumor suppressor protein p53. The model comprises of 4 ODEs, 23 unknown parameters, and noisy output measurements of the 4 state variables and the input. Three least sensitive and highly correlated parameters were isolated from the analysis and fixed to nominal values. This reduced the parameter search space and yielded substantially improved numerical identifiability properties for the resulting simplified model which fitted the data equally well, using both global and local search algorithms

Functions and genres of Chinese ESL children's English writing in school and at home

Drawing on a sociocultural perspective of genre as a social action situated in a particular context, this study examines the functions and genres of four second-grade ESL (English as a Second Language) children’s writing at home and at school. The two boys and two girls were born and raised in Canada, speaking English at school and with their siblings, and Cantonese at home with their parents who were immigrants from Hong Kong or China. A total of 67 pieces of school writing and 54 pieces of home writing were collected over a five-week period. Findings show that home writing exhibits a wider range of functions and genres than school writing. In the home context, the participating children wrote for more personal purposes, to entertain themselves, or to engage in social interactions with a real audience. In contrast, school writing narrowed the children’s choice of functions because of the teaching context, teacher expectations, and instructional objectives. Similarly, there was a greater variety in home genres, including greeting cards, diaries, notes, poems, and jokes in comparison to school genres that were confined to stories, journals, and list items. There was a strong relationship between the enactment of specific functions and particular genres while personal and social functions were more prevalent in their home-based than in their school-based writing. Qualitative analysis of the children’s writing shows that they constructed meaning with written language in individual ways in their enactment of functions and choice of genres and the use of different modes to represent meaning. The study suggests that teachers should be aware of the value of the writing opportunities and contexts children have at home and, therefore, incorporate such home experiences into classroom teaching. It also has implications for parents to conceive writing as a sociocultural as well as language practice, and to recognize the role of the home environment in their contributions to their children’s constructing meaning with written language. They should be aware of the need to build on the children’s interests and needs while encouraging them to write, and to make connections with school in working towards their writing development.Education, Faculty ofLanguage and Literacy Education (LLED), Department ofGraduat

The disconfirmation-expectancy model of hearing aid satisfaction in first time users in Hong Kong

published_or_final_versionSpeech and Hearing SciencesMasterMaster of Science in Audiolog

Degradation Parameters from Pulse-Chase Experiments

<div><p>Pulse-chase experiments are often used to study the degradation of macromolecules such as proteins or mRNA. Considerations for the choice of pulse length include the toxicity of the pulse to the cell and maximization of labeling. In the general case of non-exponential decay, varying the length of the pulse results in decay patterns that look different. Analysis of these patterns without consideration to pulse length would yield incorrect degradation parameters. Here we propose a method that constructively includes pulse length in the analysis of decay patterns and extracts the parameters of the underlying degradation process. We also show how to extract decay parameters reliably from measurements taken during the pulse phase.</p></div

Age distribution of molecules during pulse chase experiments.

<p><b>(a)</b> Depiction of molecules in a cell during a pulse chase experiment with pulse duration of 70 in arbitrary units (a.u.). For the purpose of illustration we show four snapshots of the experiment. In snapshot I (30 a.u.), pulse has just begun. The white dots depict the population of molecules already existing in the cell before the pulse. All newly synthesized molecules (red dots) are labeled by the pulse and measurable by the experimentalist. As the pulse continues in snapshot II (60 a.u.) we see more labeled molecules appear. Meanwhile, both labeled and unlabeled molecules degrade. In snapshot III (90 a.u.), the pulse has ended since some time. Newly synthesized molecules from this moment on are unlabeled. Again, both labeled and unlabeled molecules degrade. In snapshot IV (200 a.u.), all labeled molecules have degraded. Unlabeled molecules continue to be synthesized and degraded. <b>(b)</b> Age distribution of the labeled molecules, each curve corresponds to one phase in panel (a). In snapshot I, the pulse has just begun, and all molecules that are labeled by the pulse are no older than the time elapsed since the pulse has begun. In snapshot II, the pulse has been applied for some time; some labeled molecules may be quite old. In snapshot III the molecules cannot be younger than the time elapsed since pulse has been stopped. By snapshot IV, if there were molecules left, they would have that age distribution.</p

Model calibration with fabricated data.

<p><b>(a)</b> Verification of fitting procedure using simulated data separately. Using the parameters obtained from the best fit model to the data from [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155028#pone.0155028.ref009" target="_blank">9</a>] for pulse = 1 min, we fabricate sample data by calculating the abundance over time (dots) for different pulse lengths (1, 5, 30, 120, 1200 minutes) using the function that gives the decay pattern of the relative abundance <i>C</i>(Δ<i>t</i>), <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155028#pone.0155028.e017" target="_blank">Eq (16)</a>, as function of the measurement time Δ<i>t</i>. We then fit resultant decay patterns with our fitting routine. We get back the same rates that were used to simulated the data for each experiment (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155028#pone.0155028.t001" target="_blank">Table 1</a>). This shows that if the system in the background is unchanging, we can reliably extract the parameters of the system by fitting the decay patterns individually. <i>κ</i>₁₀ = 0.0109 min^{− 1}, <i>κ</i>₂₀ = 0.002 min^{− 1}, and <i>κ</i>₁₂ = 0.0189 min^{− 1}. <b>(b)</b> Simultaneous fit of pooled simulated data. Here the simulated data is augmented with a small amount of multiplicative noise, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155028#pone.0155028.e019" target="_blank">Eq (17)</a>. We fit the whole collection of data simultaneously (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155028#sec004" target="_blank">Methods</a>). Values very close to our original simulation parameters are obtained (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155028#pone.0155028.t001" target="_blank">Table 1</a> last row). This shows that under steady experimental conditions, we can reliably extract the parameters of the system by fitting the decay patterns simultaneously.</p