Fr-TM-align: a new protein structural alignment method based on fragment alignments and the TM-score

©2008 Pandit and Skolnick; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article is available from: http://www.biomedcentral.com/1471-2105/9/531doi:10.1186/1471-2105-9-531Background: Protein tertiary structure comparisons are employed in various fields of contemporary structural biology. Most structure comparison methods involve generation of an initial seed alignment, which is extended and/or refined to provide the best structural superposition between a pair of protein structures as assessed by a structure comparison metric. One such metric, the TM-score, was recently introduced to provide a combined structure quality measure of the coordinate root mean square deviation between a pair of structures and coverage. Using the TM-score, the TM-align structure alignment algorithm was developed that was often found to have better accuracy and coverage than the most commonly used structural alignment programs; however, there were a number of situations when this was not true. Results: To further improve structure alignment quality, the Fr-TM-align algorithm has been developed where aligned fragment pairs are used to generate the initial seed alignments that are then refined using dynamic programming to maximize the TM-score. For the assessment of the structural alignment quality from Fr-TM-align in comparison to other programs such as CE and TMalign, we examined various alignment quality assessment scores such as PSI and TM-score. The assessment showed that the structural alignment quality from Fr-TM-align is better in comparison to both CE and TM-align. On average, the structural alignments generated using Fr-TM-align have a higher TM-score (~9%) and coverage (~7%) in comparison to those generated by TM-align. Fr- TM-align uses an exhaustive procedure to generate initial seed alignments. Hence, the algorithm is computationally more expensive than TM-align. Conclusion: Fr-TM-align, a new algorithm that employs fragment alignment and assembly provides better structural alignments in comparison to TM-align. The source code and executables of Fr- TM-align are freely downloadable at: http://cssb.biology.gatech.edu/skolnick/files/FrTMalign/

Profiling allele-specific gene expression in brains from individuals with autism spectrum disorder reveals preferential minor allele usage.

One fundamental but understudied mechanism of gene regulation in disease is allele-specific expression (ASE), the preferential expression of one allele. We leveraged RNA-sequencing data from human brain to assess ASE in autism spectrum disorder (ASD). When ASE is observed in ASD, the allele with lower population frequency (minor allele) is preferentially more highly expressed than the major allele, opposite to the canonical pattern. Importantly, genes showing ASE in ASD are enriched in those downregulated in ASD postmortem brains and in genes harboring de novo mutations in ASD. Two regions, 14q32 and 15q11, containing all known orphan C/D box small nucleolar RNAs (snoRNAs), are particularly enriched in shifts to higher minor allele expression. We demonstrate that this allele shifting enhances snoRNA-targeted splicing changes in ASD-related target genes in idiopathic ASD and 15q11-q13 duplication syndrome. Together, these results implicate allelic imbalance and dysregulation of orphan C/D box snoRNAs in ASD pathogenesis

Differentiation and Recruitment of Th9 Cells Stimulated by Pleural Mesothelial Cells in Human Mycobacterium tuberculosis Infection

Newly discovered IL-9–producing CD4+ helper T cells (Th9 cells) have been reported to contribute to tissue inflammation and immune responses, however, differentiation and immune regulation of Th9 cells in tuberculosis remain unknown. In the present study, our data showed that increased Th9 cells with the phenotype of effector memory cells were found to be in tuberculous pleural effusion as compared with blood. TGF-β was essential for Th9 cell differentiation from naïve CD4+ T cells stimulated with PMA and ionomycin in vitro for 5 h, and addition of IL-1β, IL-4 or IL-6 further augmented Th9 cell differentiation. Tuberculous pleural effusion and supernatants of cultured pleural mesothelial cells were chemotactic for Th9 cells, and this activity was partly blocked by anti-CCL20 antibody. IL-9 promoted the pleural mesothelial cell repairing and inhibited IFN-γ-induced pleural mesothelial cell apoptosis. Moreover, pleural mesothelial cells promoted Th9 cell differentiation by presenting antigen. Collectively, these data provide new information concerning Th9 cells, in particular the collaborative immune regulation between Th9 cells and pleural mesothelial cells in human M. tuberculosis infection. In particular, pleural mesothelial cells were able to function as antigen-presenting cells to stimulate Th9 cell differentiation

Anti-apoptotic function of Xbp1 as an IL-3 signaling molecule in hematopoietic cells

Cytokine signaling is critical for proliferation, survival and differentiation of hematopoietic cell, and interleukin-3 (IL-3) is required for maintenance of many hematopoietic cell lines, such as BaF3. We have isolated apoptosis-resistant clones of BaF3 using retroviral insertional mutagenesis and the Xbp1 locus was identified as a retroviral integration site. Expression and splicing of the Xbp1 transcript was conserved in the resistant clone but was promptly disappeared on IL-3 withdrawal in parental BaF3. IL-3 stimulation of BaF3 cells enhanced Xbp1 promoter activity and induced phosphorylation of the endoplasmic reticulum stress sensor protein IRE1, resulting in the increase in Xbp1S that activates unfolded protein response. When downstream signaling from IL-3 was blocked by LY294002 and/or dn-Stat5, Xbp1 expression was downregulated and IRE1 phosphorylation was suppressed. Inhibition of IL-3 signaling as well as knockdown of Xbp1-induced apoptosis in BaF3 cells. In contrast, constitutive expression of Xbp1S protected BaF3 from apoptosis during IL-3 depletion. However, cell cycle arrest at the G1 stage was observed in BaF3 and myeloid differentiation was induced in IL-3-dependent 32Dcl3 cells. Expression of apoptosis-, cell cycle- and differentiation-related genes was modulated by Xbp1S expression. These results indicate that the proper transcriptional and splicing regulation of Xbp1 by IL-3 signaling is important in homeostasis of hematopoietic cells

Analysis of the Human Kinome Using Methods Including Fold Recognition Reveals Two Novel Kinases

Background: Protein sequence similarity is a commonly used criterion for inferring the unknown function of a protein from a protein of known function. However, proteins can diverge significantly over time such that sequence similarity is difficult, if not impossible, to find. In some cases, a structural similarity remains over long evolutionary time scales and once detected can be used to predict function. Methodology/Principal Findings: Here we employed a high-throughput approach to assign structural and functional annotation to the human proteome, focusing on the collection of human protein kinases, the human kinome. We compared human protein sequences to a library of domains from known structures using WU-BLAST, PSI-BLAST, and 123D. This approach utilized both sequence comparison and fold recognition methods. The resulting set of potential protein kinases was cross-checked against previously identified human protein kinases, and analyzed for conserved kinase motifs. Conclusions/Significance: We demonstrate that our structure-based method can be used to identify both typical and atypical human protein kinases. We also identify two potentially novel kinases that contain an interesting combination o

Surface-enhanced Raman spectroscopy study of 4-ATP on gold nanoparticles for basal cell carcinoma fingerprint detection

The surface-enhanced Raman signals of 4-aminothiophenol (4-ATP) attached to the surface of colloidal gold nanoparticles with size distribution of 2 to 5 nm were used as a labeling agent to detect basal cell carcinoma (BCC) of the skin. The enhanced Raman band at 1075 cm-1 corresponding to the C-S stretching vibration in 4-ATP was observed during attachment to the surface of the gold nanoparticles. The frequency and intensity of this band did not change when the colloids were conjugated with BerEP4 antibody, which specifically binds to BCC. We show the feasibility of imaging BCC by surface-enhanced Raman spectroscopy, scanning the 1075 cm-1 band to detect the distribution of 4ATP-coated gold nanoparticles attached to skin tissue ex vivo

Service workload patterns for QoS-driven cloud resource management

Cloud service providers negotiate SLAs for customer services they offer based on the reliability of performance and availability of their lower-level platform infrastructure. While availability management is more mature, performance management is less reliable. In order to support a continuous approach that supports the initial static infrastructure configuration as well as dynamic reconfiguration and auto-scaling, an accurate and efficient solution is required. We propose a prediction technique that combines a workload pattern mining approach with a traditional collaborative filtering solution to meet the accuracy and efficiency requirements. Service workload patterns abstract common infrastructure workloads from monitoring logs and act as a part of a first-stage high-performant configuration mechanism before more complex traditional methods are considered. This enhances current reactive rule-based scalability approaches and basic prediction techniques by a hybrid prediction solution. Uncertainty and noise are additional challenges that emerge in multi-layered, often federated cloud architectures. We specifically add log smoothing combined with a fuzzy logic approach to make the prediction solution more robust in the context of these challenges

Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward

Decision-making on numerous aspects of our daily lives is being outsourced to machine-learning algorithms and artificial intelligence (AI), motivated by speed and efficiency in the decision process. Machine learning (ML) approaches - one of the typologies of algorithms underpinning artificial intelligence - are typically developed as black boxes. The implication is that ML code scripts are rarely scrutinised; interpretability is usually sacrificed in favour of usability and effectiveness. Room for improvement in practices associated with programme development have also been flagged along other dimensions, including inter alia fairness, accuracy, accountability, and transparency. In this contribution, the production of guidelines and dedicated documents around these themes is discussed. The following applications of AI-driven decision making are outlined: a) Risk assessment in the criminal justice system, and b) autonomous vehicles, highlighting points of friction across ethical principles. Possible ways forward towards the implementation of governance on AI are finally examined