Mining Proteins with Non-Experimental Annotations Based on an Active Sample Selection Strategy for Predicting Protein Subcellular Localization

Subcellular localization of a protein is important to understand proteins’ functions and interactions. There are many techniques based on computational methods to predict protein subcellular locations, but it has been shown that many prediction tasks have a training data shortage problem. This paper introduces a new method to mine proteins with non-experimental annotations, which are labeled by non-experimental evidences of protein databases to overcome the training data shortage problem. A novel active sample selection strategy is designed, taking advantage of active learning technology, to actively find useful samples from the entire data pool of candidate proteins with non-experimental annotations. This approach can adequately estimate the “value” of each sample, automatically select the most valuable samples and add them into the original training set, to help to retrain the classifiers. Numerical experiments with for four popular multi-label classifiers on three benchmark datasets show that the proposed method can effectively select the valuable samples to supplement the original training set and significantly improve the performances of predicting classifiers.     

Investigating the Effects of Food Available and Climatic Variables on the Animal Host Density of Hemorrhagic Fever with Renal Syndrome in Changsha,China

Background

The transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by population dynamics of its main host, rodents. It is therefore important to better understand rodents’ characteristic in epidemic areas.

Methodology/Principal Findings

We examined the potential impact of food available and climatic variability on HFRS rodent host and developed forecasting models. Monthly rodent density of HFRS host and climate data in Changsha from January 2004 to December 2011 were obtained. Monthly normalized difference vegetation index (NDVI) and temperature vegetation dryness index (TVDI) for rice paddies were extracted from MODIS data. Cross-correlation analysis were carried out to explore correlation between climatic variables and food available with monthly rodent data. We used auto-regressive integrated moving average model with explanatory variables to examine the independent contribution of climatic variables and food supply to rodent density. The results indicated that relative rodent density of HFRS host was significantly correlated with monthly mean temperatures, monthly accumulative precipitation, TVDI and NDVI with lags of 1–6 months.

Conclusions/Significance

Food available plays a significant role in population fluctuations of HFRS host in Changsha. The model developed in this study has implications for HFRS control and prevention.     

Real Time Assays for Quantifying Cytotoxicity with Single Cell Resolution

A new live cell-based assay platform has been developed for the determination of complement dependent cytotoxicity (CDC), antibody dependent cellular cytotoxicity (ADCC), and overall cytotoxicity in human whole blood. In these assays, the targeted tumor cell populations are first labeled with fluorescent Cell Tracker dyes and immobilized using a DNA-based adhesion technique. This allows the facile generation of live cell arrays that are arranged arbitrarily or in ordered rectilinear patterns. Following the addition of antibodies in combination with serum, PBMCs, or whole blood, cell death within the targeted population can be assessed by the addition of propidium iodide (PI) as a viability probe. The array is then analyzed with an automated microscopic imager. The extent of cytotoxicity can be quantified accurately by comparing the number of surviving target cells to the number of dead cells labeled with both Cell Tracker and PI. Excellent batch-to-batch reproducibility has been achieved using this method. In addition to allowing cytotoxicity analysis to be conducted in real time on a single cell basis, this new assay overcomes the need for hazardous radiochemicals. Fluorescently-labeled antibodies can be used to identify individual cells that bear the targeted receptors, but yet resist the CDC and ADCC mechanisms. This new approach also allows the use of whole blood in cytotoxicity assays, providing an assessment of antibody efficacy in a highly relevant biological mixture. Given the rapid development of new antibody-based therapeutic agents, this convenient assay platform is well-poised to streamline the drug discovery process significantly.     

End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis

Background

Synthetic biology aims to engineer biological systems for desired behaviors. The construction of these systems can be complex, often requiring genetic reprogramming, extensive de novo DNA synthesis, and functional screening.

Results

Herein, we present a programmable, multipurpose microfluidic platform and associated software and apply the platform to major steps of the synthetic biology research cycle: design, construction, testing, and analysis. We show the platform’s capabilities for multiple automated DNA assembly methods, including a new method for Isothermal Hierarchical DNA Construction, and for Escherichia coli and Saccharomyces cerevisiae transformation. The platform enables the automated control of cellular growth, gene expression induction, and proteogenic and metabolic output analysis.

Conclusions

Taken together, we demonstrate the microfluidic platform’s potential to provide end-to-end solutions for synthetic biology research, from design to functional analysis.

     

Novel extracellular and nuclear caspase-1 and inflammasomes propagate inflammation and regulate gene expression: a comprehensive database mining study

Background

Caspase-1 is present in the cytosol as an inactive zymogen and requires the protein complexes named “inflammasomes” for proteolytic activation. However, it remains unclear whether the proteolytic activity of caspase-1 is confined only to the cytosol where inflammasomes are assembled to convert inactive pro-caspase-1 to active caspase-1.

Methods

We conducted meticulous data analysis method?s on proteomic, protein interaction, protein intracellular localization, and gene expressions of 114 experimentally identified caspase-1 substrates and 38 caspase-1 interaction proteins in normal physiological conditions and in various pathologies.

Results

We made the following important findings: (1) Caspase-1 substrates and interaction proteins are localized in various intracellular organelles including nucleus and secreted extracellularly; (2) Caspase-1 may get activated in situ in the nucleus in response to intra-nuclear danger signals; (3) Caspase-1 cleaves its substrates in exocytotic secretory pathways including exosomes to propagate inflammation to neighboring and remote cells; (4) Most of caspase-1 substrates are upregulated in coronary artery disease regardless of their subcellular localization but the majority of metabolic diseases cause no significant expression changes in caspase-1 nuclear substrates; and (5) In coronary artery disease, majority of upregulated caspase-1 extracellular substrate-related pathways are involved in induction of inflammation; and in contrast, upregulated caspase-1 nuclear substrate-related pathways are more involved in regulating cell death and chromatin regulation.

Conclusions

Our identification of novel caspase-1 trafficking sites, nuclear and extracellular inflammasomes, and extracellular caspase-1-based inflammation propagation model provides a list of targets for the future development of new therapeutics to treat cardiovascular diseases, inflammatory diseases, and inflammatory cancers.

     

High IKZF1/3 protein expression is a favorable prognostic factor for survival of relapsed/refractory multiple myeloma patients treated with lenalidomide

The aim of this study is to assess nucleoprotein expression of IKZF1/3 in patients with relapsed/refractory multiple myeloma (MM) who received lenalidomide-based therapy and correlated them with their clinical outcomes. A total of 50 patients diagnosed with MM were entered in the study with the median follow-up of 86.4 months. By immunohistochemistry (IHC), IKZF1 and IKZF3 were expressed in 72 and 58% of the cases, respectively. IKZF1 and IKZF3 expressions were associated with longer median progression free survival (P?=?0.0029 and P?<?0.0001) and overall survival (P?=?0.0014 and P?<?0.0001). IKZF3 expression also appears predicted a favorable response to the lenalidomide-based therapy.     

An Efficient Supervised Training Algorithm for Multilayer Spiking Neural Networks

The spiking neural networks (SNNs) are the third generation of neural networks and perform remarkably well in cognitive tasks such as pattern recognition. The spike emitting and information processing mechanisms found in biological cognitive systems motivate the application of the hierarchical structure and temporal encoding mechanism in spiking neural networks, which have exhibited strong computational capability. However, the hierarchical structure and temporal encoding approach require neurons to process information serially in space and time respectively, which reduce the training efficiency significantly. For training the hierarchical SNNs, most existing methods are based on the traditional back-propagation algorithm, inheriting its drawbacks of the gradient diffusion and the sensitivity on parameters. To keep the powerful computation capability of the hierarchical structure and temporal encoding mechanism, but to overcome the low efficiency of the existing algorithms, a new training algorithm, the Normalized Spiking Error Back Propagation (NSEBP) is proposed in this paper. In the feedforward calculation, the output spike times are calculated by solving the quadratic function in the spike response model instead of detecting postsynaptic voltage states at all time points in traditional algorithms. Besides, in the feedback weight modification, the computational error is propagated to previous layers by the presynaptic spike jitter instead of the gradient decent rule, which realizes the layer-wised training. Furthermore, our algorithm investigates the mathematical relation between the weight variation and voltage error change, which makes the normalization in the weight modification applicable. Adopting these strategies, our algorithm outperforms the traditional SNN multi-layer algorithms in terms of learning efficiency and parameter sensitivity, that are also demonstrated by the comprehensive experimental results in this paper.     

The Effect of Codon Mismatch on the Protein Translation System

Incorrect protein translation, caused by codon mismatch, is an important problem of living cells. In this work, a computational model was introduced to quantify the effects of codon mismatch and the model was used to study the protein translation of Saccharomyces cerevisiae. According to simulation results, the probability of codon mismatch will increase when the supply of amino acids is unbalanced, and the longer is the codon sequence, the larger is the probability for incorrect translation to occur, making the synthesis of long peptide chain difficult. By comparing to simulation results without codon mismatch effects taken into account, the fraction of mRNAs with bound ribosome decrease faster along the mRNAs, making the 5’ ramp phenomenon more obvious. It was also found in our work that the premature mechanism resulted from codon mismatch can reduce the proportion of incorrect translation when the amino acid supply is extremely unbalanced, which is one possible source of high fidelity protein synthesis after peptidyl transfer.     

Comparison of three transgenic Bt rice lines for insecticidal protein expression and resistance against a target pest,Chilo suppressalis (Lepidoptera: Crambidae)

Two transgenic rice lines (T2A‐1 and T1C‐19b) expressing cry2A and cry1C genes, respectively, were developed in China, targeting lepidopteran pests including Chilo suppressalis (Walker) (Lepidoptera: Crambidae). The seasonal expression of Cry proteins in different tissues of the rice lines and their resistance to C. suppressalis were assessed in comparison to a Bt rice line expressing a cry1Ab/Ac fusion gene, Huahui 1, which has been granted a biosafety certificate. In general, levels of Cry proteins were T2A‐1 > Huahui 1 > T1C‐19b among rice lines, and leaf > stem > root among rice tissues. The expression patterns of Cry protein in the rice line plants were similar: higher level at early stages than at later stages with an exception that high Cry1C level in T1C‐19b stems at the maturing stage. The bioassay results revealed that the three transgenic rice lines exhibited significantly high resistance against C. suppressalis larvae throughout the rice growing season. According to Cry protein levels in rice tissues, the raw and corrected mortalities of C. suppressalis caused by each Bt rice line were the highest in the seedling and declined through the jointing stage with an exception for T1C‐19b providing an excellent performance at the maturing stage. By comparison, T1C‐19b exhibited more stable and greater resistance to C. suppressalis larvae than T2A‐1, being close to Huahui 1. The results suggest cry1C is an ideal Bt gene for plant transformation for lepidopteran pest control, and T1C‐19b is a promising Bt rice line for commercial use for tolerating lepidopteran rice pests.