Evolutionary Graph Clustering for Protein Complex Identification

This paper presents a graph clustering algorithm, called EGCPI, to discover protein complexes in protein-protein interaction (PPI) networks. In performing its task, EGCPI takes into consideration both network topologies and attributes of interacting proteins, both of which have been shown to be important for protein complex discovery. EGCPI formulates the problem as an optimization problem and tackles it with evolutionary clustering. Given a PPI network, EGCPI first annotates each protein with corresponding attributes that are provided in Gene Ontology database. It then adopts a similarity measure to evaluate how similar the connected proteins are taking into consideration the network topology. Given this measure, EGCPI then discovers a number of graph clusters within which proteins are densely connected, based on an evolutionary strategy. At last, EGCPI identifies protein complexes in each discovered cluster based on the homogeneity of attributes performed by pairwise proteins. EGCPI has been tested with several real data sets and the experimental results show EGCPI is very effective on protein complex discovery, and the evolutionary clustering is helpful to identify protein complexes in PPI networks. The software of EGCPI can be downloaded via: https://github.com/hetiantian1985/EGCPI.

WSB-1 regulates the metastatic potential of hormone receptor negative breast cancer

BACKGROUND

Metastatic spread is responsible for the majority of cancer-associated deaths. The tumour microenvironment, including hypoxia, is a major driver of metastasis. The aim of this study was to investigate the role of the E3 ligase WSB-1 in breast cancer biology in the context of the hypoxic tumour microenvironment, particularly regarding metastatic spread.

METHODS

In this study, WSB-1 expression was evaluated in breast cancer cell lines and patient samples. In silico analyses were used to determine the impact of WSB-1 expression on distant metastasis-free survival (DMFS) in patients, and correlation between WSB1 expression and hypoxia gene expression signatures. The role of WSB-1 on metastasis promotion was evaluated in vitro and in vivo.

RESULTS

High WSB1 expression was associated with decreased DMFS in ER-breast cancer and PR-breast cancer patients. Surprisingly, WSB1 expression was not positively correlated with known hypoxic gene expression signatures in patient samples. Our study is the first to show that WSB-1 knockdown led to decreased metastatic potential in breast cancer hormone receptor-negative models in vitro and in vivo. WSB-1 knockdown was associated with decreased metalloproteinase (MMP) activity, vascular endothelial growth factor (VEGF) secretion, and angiogenic potential.

CONCLUSIONS

Our data suggests that WSB-1 may be an important regulator of aggressive metastatic disease in hormone receptor-negative breast cancer. WSB-1 could therefore represent a novel regulator and therapeutic target for secondary breast cancer in these patients.

Radical and lunatic fringes modulate notch ligands to support mammalian intestinal homeostasis

Notch signalling maintains stem cell regeneration at the mouse intestinal crypt base and balances the absorptive and secretory lineages in the upper crypt and villus. Here we report the role of Fringe family of glycosyltransferases in modulating Notch activity in the two compartments. At the crypt base, RFNG is enriched in the Paneth cells and increases cell surface expression of DLL1 and DLL4. This promotes Notch activity in the neighbouring Lgr5+ stem cells assisting their self-renewal. Expressed by various secretory cells in the upper crypt and villus, LFNG promotes DLL surface expression and suppresses the secretory lineage . Hence, in the intestinal epithelium, Fringes are present in the ligand-presenting 'sender' secretory cells and promote Notch activity in the neighbouring 'receiver' cells. Fringes thereby provide for targeted modulation of Notch activity and thus the cell fate in the stem cell zone, or the upper crypt and villus.

Chronic diazoxide treatment decreases fat mass and improves endurance capacity in an obese mouse model of Prader-Willi syndrome

Excess fat mass is a cardinal feature of Prader-Willi syndrome (PWS) that is recapitulated in the Magel2-null mouse model of this genetic disorder. There is a pressing need for drugs that can prevent or treat obesity in children with PWS. Recently, a clinical study of a controlled release form of the benzothiadiazine derivative diazoxide demonstrated improved metabolic parameters and decreased fat mass in obese children and adults with PWS. We tested whether chronic diazoxide administration can reduce fat mass and improve metabolism in mice lacking MAGEL2, a gene inactivated in PWS. Magel2-null and wild-type control mice were rendered obese by high fat diet feeding, then provided diazoxide while being maintained on a high fat diet. Treatment of obese mice with diazoxide reduced weight and body fat, lowered blood glucose and improved endurance capacity. Treatment with diazoxide partially normalizes obesity in children and adults with PWS and in a PWS mouse model, demonstrating that the biological pathways impacted by diazoxide may be rational pharmacological targets in PWS and other disorders diseases associated with obesity.

Structural prediction of protein models using distance restraints derived from cross-linking mass spectrometry data

This protocol describes a workflow for creating structural models of proteins or protein complexes using distance restraints derived from cross-linking mass spectrometry experiments. The distance restraints are used (i) to adjust preliminary models that are calculated on the basis of a homologous template and primary sequence, and (ii) to select the model that is in best agreement with the experimental data. In the case of protein complexes, the cross-linking data are further used to dock the subunits to one another to generate models of the interacting proteins. Predicting models in such a manner has the potential to indicate multiple conformations and dynamic changes that occur in solution. This modeling protocol is compatible with many cross-linking workflows and uses open-source programs or programs that are free for academic users and do not require expertise in computational modeling. This protocol is an excellent additional application with which to use cross-linking results for building structural models of proteins. The established protocol is expected to take 6-12 d to complete, depending on the size of the proteins and the complexity of the cross-linking data.

A paralogous pair of mammalian host restriction factors form a critical host barrier against poxvirus infection

Host restriction factors constitute a formidable barrier for viral replication to which many viruses have evolved counter-measures. Human SAMD9, a tumor suppressor and a restriction factor for poxviruses in cell lines, is antagonized by two classes of poxvirus proteins, represented by vaccinia virus (VACV) K1 and C7. A paralog of SAMD9, SAMD9L, is also encoded by some mammals, while only one of two paralogs is retained by others. Here, we show that SAMD9L functions similarly to SAMD9 as a restriction factor and that the two paralogs form a critical host barrier that poxviruses must overcome to establish infection. In mice, which naturally lack SAMD9, overcoming SAMD9L restriction with viral inhibitors is essential for poxvirus replication and pathogenesis. While a VACV deleted of both K1 and C7 (vK1L^-C7L^-) was restricted by mouse cells and highly attenuated in mice, its replication and virulence were completely restored in SAMD9L^-/- mice. In humans, both SAMD9 and SAMD9L are poxvirus restriction factors, although the latter requires interferon induction in many cell types. While knockout of SAMD9 with Crispr-Cas9 was sufficient for abolishing the restriction for vK1L^-C7L^- in many human cells, knockout of both paralogs was required for abolishing the restriction in interferon-treated cells. Both paralogs are antagonized by VACV K1, C7 and C7 homologs from diverse mammalian poxviruses, but mouse SAMD9L is resistant to the C7 homolog encoded by a group of poxviruses with a narrow host range in ruminants, indicating that host species-specific difference in SAMD9/SAMD9L genes serves as a barrier for cross-species poxvirus transmission.

Zoonotic viral infections represent a major threat to public health. For many viruses, host species-specific difference in viral entry receptors presents a major hurdle for cross-species transmission. Poxviruses, however, can enter nearly any animal cell. Why many poxviruses show strict host species specificity and what it would take for them to jump to new hosts are less clear. Here, we present data suggesting that SAMD9 and its paralog, SAMD9L, constitute a critical host barrier against poxvirus infection and pathogenesis. We also discovered some host species-specific difference in SAMD9/SAMD9L and some poxvirus-specific difference in antagonizing SAMD9/SAMD9L, suggesting that these differences serve as a barrier for cross-species poxvirus infection. The knowledge is fundamental for understanding the determinants of poxvirus host-range.

[From sequence variability to structural and functional prediction: modeling of homologous protein families]

Thanks to next-generation sequencing, the number of sequenced genomes grows rapidly, providing in particular ample examples for the sequence variability between homologous proteins. This article discusses data-driven probabilistic sequence models, which are able to extract a multitude of information from sequence data alone, including (i) structural features like residue-residue contacts, which are formed in the folded protein, (ii) protein-protein interaction interfaces and (iii) phenotypic effects of amino-acid substitutions in proteins.

Multiplexed gene synthesis in emulsions for exploring protein functional landscapes

Improving our ability to construct and functionally characterize DNA sequences would broadly accelerate progress in biology. Here, we introduce DropSynth, a scalable, low-cost method to build thousands of defined gene-length constructs in a pooled (multiplexed) manner. DropSynth uses a library of barcoded beads that pull down the oligonucleotides necessary for a gene's assembly, which are then processed and assembled in water-in-oil emulsions. We used DropSynth to successfully build more than 7000 synthetic genes that encode phylogenetically diverse homologs of two essential genes in Escherichia coli We tested the ability of phosphopantetheine adenylyltransferase homologs to complement a knockout E. coli strain in multiplex, revealing core functional motifs and reasons underlying homolog incompatibility. DropSynth coupled with multiplexed functional assays allows us to rationally explore sequence-function relationships at an unprecedented scale.

Distinct expression of functionally glycosylated alpha-dystroglycan in muscle and non-muscle tissues of FKRP mutant mice

The glycosylation of alpha-dystroglycan (α-DG) is crucial in maintaining muscle cell membrane integrity. Dystroglycanopathies are identified by the loss of this glycosylation leading to a breakdown of muscle cell membrane integrity and eventual degeneration. However, a small portion of fibers expressing functionally glycosylated α-DG (F-α-DG) (revertant fibers, RF) have been identified. These fibers are generally small in size, centrally nucleated and linked to regenerating fibers. Examination of different muscles have shown various levels of RFs but it is unclear the extent of which they are present. Here we do a body-wide examination of muscles from the FKRP-P448L mutant mouse for the prevalence of RFs. We have identified great variation in the distribution of RF in different muscles and tissues. Triceps shows a large increase in RFs and together with centrally nucleated fibers whereas the pectoralis shows a reduction in revertant but increase in centrally nucleated fibers from 6 weeks to 6 months of age. We have also identified that the sciatic nerve with near normal levels of F-α-DG in the P448Lneo- mouse with reduced levels in the P448Lneo+ and absent in LARGE^myd. The salivary gland of LARGE^myd mice expresses high levels of F-α-DG. Interestingly the same glands in the P448Lneo-and to a lesser degree in P448Lneo+ also maintain considerable amount of F-α-DG, indicating the non-proliferating epithelial cells have a molecular setting permitting glycosylation.

[The role of «Youth and aging proteins» in essential hypertension pathogenesis.]

Essential hypertension (EG) is an age-associated disease. Often EG of elderly patients haven't good way of treatment. Thus, the search of new target molecules for EG therapy is an actual goal of gerontology and molecular medicine. It was shown, that during EG concentrations of GDF11 «youth protein» decreased in 3,3 times and GDF15, JAM-A/1, CCL11 «aging proteins» increased in 1,4-2,4 times. EG patients have abnormal microcirculation processes. It was shown as decreasing in 1,3 and 1,7 times of hemodynamic HI1 and H1-H3 indexes. EG patients have negative correlation of GDF15 concentration with arterial pressure. EG patients have no correlation of JAM-A/1 concentration with arterial pressure. Normal is positive correlation with GDF15, JAM-A/1 concentration with arterial pressure. GDF15 blood level during EG have positive correlation with HI1-HI3 and negative correlation with NEUR_HI2 and MAYER_HI3 indexes. It can show on pathogenesis mechanisms of endothelial and smooth muscles function of vessels tissues. We suppose, that the regulation of GDF11, GDF15, JAM-A/1, CCL11 «youth and aging proteins» can be target object of EG therapy.

Inferring the Functions of Proteins from the Interrelationships between Functional Categories

This study proposes a new method to determine the functions of an unannotated protein. The proteins and amino acid residues mentioned in biomedical texts associated with an unannotated protein can be considered as characteristics terms for , which are highly predictive of the potential functions of . Similarly, proteins and amino acid residues mentioned in biomedical texts associated with proteins annotated with a functional category can be considered as characteristics terms of . We introduce in this paper an information extraction system called IFP_IFC that predicts the functions of an unannotated protein by representing and each functional category by a vector of weights. Each weight reflects the degree of association between a characteristic term and (or a characteristic term and ). First, IFP_IFC constructs a network, whose nodes represent the different functional categories, and its edges the interrelationships between the nodes. Then, it determines the functions of by employing random walks with restarts on the mentioned network. The walker is the vector of . Finally, is assigned to the functional categories of the nodes in the network that are visited most by the walker. We evaluated the quality of IFP_IFC by comparing it experimentally with two other systems. Results showed marked improvement.

Ultrasonic Characteristics and Cellular Properties of Anabaena Gas Vesicles

Ultrasound imaging is a common modality in clinical examination and biomedical research, but has not played a significant role in molecular imaging for lack of an appropriate contrast agent. Recently, biogenic gas vesicles (GVs), naturally formed by cyanobacteria and haloarchaea, have exhibited great potential as an ultrasound molecular imaging probe with a much smaller size (∼100 nm) and improved imaging contrast. However, the basic acoustic and biological properties of GVs remain unclear, which hinders future application. Here, we studied the fundamental acoustic properties of a rod-shaped gas vesicle from Anabaena, a kind of cyanobacterium, including attenuation, oscillation resonance, and scattering, as well as biological behaviors (cellular internalization and cytotoxicity). We found that GVs have two resonance peaks (85 and 120 MHz). We also observed a significant non-linear effect and its pressure dependence as well. Ultrasound B-mode imaging reveals sufficient echogenicity of GVs for ultrasound imaging enhancement at high frequencies. Biological characterization also reveals endocytosis and non-toxicity.

Predictive model identifies key network regulators of cardiomyocyte mechano-signaling

Mechanical strain is a potent stimulus for growth and remodeling in cells. Although many pathways have been implicated in stretch-induced remodeling, the control structures by which signals from distinct mechano-sensors are integrated to modulate hypertrophy and gene expression in cardiomyocytes remain unclear. Here, we constructed and validated a predictive computational model of the cardiac mechano-signaling network in order to elucidate the mechanisms underlying signal integration. The model identifies calcium, actin, Ras, Raf1, PI3K, and JAK as key regulators of cardiac mechano-signaling and characterizes crosstalk logic imparting differential control of transcription by AT1R, integrins, and calcium channels. We find that while these regulators maintain mostly independent control over distinct groups of transcription factors, synergy between multiple pathways is necessary to activate all the transcription factors necessary for gene transcription and hypertrophy. We also identify a PKG-dependent mechanism by which valsartan/sacubitril, a combination drug recently approved for treating heart failure, inhibits stretch-induced hypertrophy, and predict further efficacious pairs of drug targets in the network through a network-wide combinatorial search.

Common stresses such as high blood pressure or heart attack can lead to heart failure, which afflicts over 25 million people worldwide. These stresses cause cardiomyocytes to grow and remodel, which may initially be beneficial but ultimately worsen heart function. Current heart failure drugs such as beta-blockers counteract biochemical cues prompting cardiomyocyte growth, yet mechanical cues to cardiomyocytes such as stretch are just as important in driving cardiac dysfunction. However, no pharmacological treatments have yet been approved that specifically target mechano-signaling, in part because it is not clear how cardiomyocytes integrate signals from multiple mechano-responsive sensors and pathways into their decision to grow. To address this challenge, we built a systems-level computational model that represents 125 interactions between 94 stretch-responsive signaling molecules. The model correctly predicts 134 of 172 previous independent experimental observations, and identifies the key regulators of stretch-induced cardiomyocyte remodeling. Although cardiomyocytes have many mechano-signaling pathways that function largely independently, we find that cooperation between them is necessary to cause growth and remodeling. We identify mechanisms by which a recently approved heart failure drug pair affects mechano-signaling, and we further predict additional pairs of drug targets that could be used to help reverse heart failure.

Immature colon carcinoma transcript-1 promotes proliferation of gastric cancer cells

Gastric cancer is the fourth most common malignant tumor and has been considered as one of the leading causes of cancer-related death worldwide. The identification of the molecular mechanism during gastric cancer progression is urgently needed, which will help to develop more effective treatment strategies. As a component of the human mitoribosome, immature colon carcinoma transcript-1 (ICT1) might be involved in tumor formation and progression. However, its biological function and the corresponding mechanism in gastric cancer have been poorly characterized. To study the mechanism of ICT1 in gastric cancer, we first investigated the mRNA levels of ICT1 in human normal and gastric cancer tissues using datasets from the publicly available Oncomine database. The results showed that ICT1 is overexpressed in gastric cancer tissues. Then in order to study the role of ICT1 in gastric cancer, two shRNAs were used to silence ICT1 in MGC80-3 and AGS cells. Functional analysis showed ICT1 knockdown significantly inhibited the proliferation of gastric cancer cells and induced apoptosis. Further, mechanistic study demonstrated that ICT1 silencing induced cell-cycle arrest at G2/M phase via the suppression of cyclin A2 and cyclin B1. In addition, ICT1 silencing also increased cleaved caspase-3 and activated PARP in gastric cancer cells. These findings suggest that ICT1 may play a crucial role in promoting gastric cancer proliferation in vitro.

IL-22 induces Reg3γ and inhibits allergic inflammation in house dust mite-induced asthma models

Previous studies have shown that IL-22, one of the Th17 cell-related cytokines, plays multiple roles in regulating allergic airway inflammation caused by antigen-specific Th2 cells; however, the underlying mechanism remains unclear. Here, we show that allergic airway inflammation and Th2 and Th17 cytokine production upon intratracheal administration of house dust mite (HDM) extract, a representative allergen, were exacerbated in IL-22-deficient mice. We also found that IL-22 induces Reg3γ production from lung epithelial cells through STAT3 activation and that neutralization of Reg3γ significantly exacerbates HDM-induced eosinophilic airway inflammation and Th2 cytokine induction. Moreover, exostatin-like 3 (EXTL3), a functional Reg3γ binding protein, is expressed in lung epithelial cells, and intratracheal administration of recombinant Reg3γ suppresses HDM-induced thymic stromal lymphopoietin and IL-33 expression and accumulation of type 2 innate lymphoid cells in the lung. Collectively, these results suggest that IL-22 induces Reg3γ production from lung epithelial cells and inhibits the development of HDM-induced allergic airway inflammation, possibly by inhibiting cytokine production from lung epithelial cells.

Functional roles of the pepper leucine-rich repeat protein and its interactions with pathogenesis-related and hypersensitive-induced proteins in plant cell death and immunity

Pepper leucine-rich repeat protein (CaLRR1) interacts with defense response proteins to regulate plant cell death and immunity. This review highlights the current understanding of the molecular functions of CaLRR1 and its interactor proteins. Plant cell death and immune responses to microbial pathogens are controlled by complex and tightly regulated molecular signaling networks. Xanthomonas campestris pv. vesicatoria (Xcv)-inducible pepper (Capsicum annuum) leucine-rich repeat protein 1 (CaLRR1) serves as a molecular marker for plant cell death and immunity signaling. In this review, we discuss recent advances in elucidating the functional roles of CaLRR1 and its interacting plant proteins, and understanding how they are involved in the cell death and defense responses. CaLRR1 physically interacts with pepper pathogenesis-related proteins (CaPR10 and CaPR4b) and hypersensitive-induced reaction protein (CaHIR1) to regulate plant cell death and defense responses. CaLRR1 is produced in the cytoplasm and trafficked to the extracellular matrix. CaLRR1 binds to CaPR10 in the cytoplasm and CaPR4b and CaHIR1 at the plasma membrane. CaLRR1 synergistically accelerates CaPR10-triggered hypersensitive cell death, but negatively regulates CaPR4b- and CaHIR1-triggered cell death. CaHIR1 interacts with Xcv filamentous hemagglutinin (Fha1) to trigger disease-associated cell death. The subcellular localization and cellular function of these CaLRR1 interactors during plant cell death and defense responses were elucidated by Agrobacterium-mediated transient expression, virus-induced gene silencing, and transgenic overexpression studies. CaPR10, CaPR4b, and CaHIR1 positively regulate defense signaling mediated by salicylic acid and reactive oxygen species, thereby activating hypersensitive cell death and disease resistance. A comprehensive understanding of the molecular functions of CaLRR1 and its interacting protein partners in cell death and defense responses will provide valuable information for the molecular genetics of plant disease resistance, which could be exploited as a sustainable disease management strategy.

Fuento: functional enrichment for bioinformatics

SUMMARY

The currently available functional enrichment software focuses mostly on gene expression analysis, whereby server- and graphical-user-interface-based tools with specific scope dominate the field. Here we present an efficient, user-friendly, multifunctional command-line-based functional enrichment tool (fu-en-to), tailored for the bioinformatics researcher.

AVAILABILITY AND IMPLEMENTATION

Source code and binaries freely available for download at github.com/DavidWeichselbaum/fuento, implemented in C ++ and supported on Linux and OS X.

CONTACT

newant@gmail.com or bojan.zagrovic@univie.ac.at.

The Niemann-Pick C1 gene interacts with a high-fat diet to promote weight gain through differential regulation of central energy metabolism pathways

A genome-wide association study (GWAS) reported that common variation in the human Niemann-Pick C1 gene (NPC1) is associated with morbid adult obesity. This study was confirmed using our BALB/cJ Npc1 mouse model, whereby heterozygous mice (Npc1^+/- ) with decreased gene dosage were susceptible to weight gain when fed a high-fat diet (HFD) compared with homozygous normal mice (Npc1^+/+ ) fed the same diet. The objective for our current study was to validate this Npc1 gene-diet interaction using statistical modeling with fitted growth trajectories, conduct body weight analyses for different measures, and define the physiological basis responsible for weight gain. Metabolic phenotype analysis indicated no significant difference between Npc1^+/+ and Npc1^+/- mice fed a HFD for food and water intake, oxygen consumption, carbon dioxide production, locomotor activity, adaptive thermogenesis, and intestinal lipid absorption. However, the livers from Npc1^+/- mice had significantly increased amounts of mature sterol regulatory element-binding protein-1 (SREBP-1) and increased expression of SREBP-1 target genes that regulate glycolysis and lipogenesis with an accumulation of triacylglycerol and cholesterol. Moreover, white adipose tissue from Npc1^+/- mice had significantly decreased amounts of phosphorylated hormone-sensitive lipase with decreased triacylglycerol lipolysis. Consistent with these results, cellular energy metabolism studies indicated that Npc1^+/- fibroblasts had significantly increased glycolysis and lipogenesis, in addition to significantly decreased substrate (glucose and endogenous fatty acid) oxidative metabolism with an accumulation of triacylglycerol and cholesterol. In conclusion, these studies demonstrate that the Npc1 gene interacts with a HFD to promote weight gain through differential regulation of central energy metabolism pathways.

When loss-of-function is loss of function: assessing mutational signatures and impact of loss-of-function genetic variants

MOTIVATION

Loss-of-function genetic variants are frequently associated with severe clinical phenotypes, yet many are present in the genomes of healthy individuals. The available methods to assess the impact of these variants rely primarily upon evolutionary conservation with little to no consideration of the structural and functional implications for the protein. They further do not provide information to the user regarding specific molecular alterations potentially causative of disease.

RESULTS

To address this, we investigate protein features underlying loss-of-function genetic variation and develop a machine learning method, MutPred-LOF, for the discrimination of pathogenic and tolerated variants that can also generate hypotheses on specific molecular events disrupted by the variant. We investigate a large set of human variants derived from the Human Gene Mutation Database, ClinVar and the Exome Aggregation Consortium. Our prediction method shows an area under the Receiver Operating Characteristic curve of 0.85 for all loss-of-function variants and 0.75 for proteins in which both pathogenic and neutral variants have been observed. We applied MutPred-LOF to a set of 1142 de novo vari3ants from neurodevelopmental disorders and find enrichment of pathogenic variants in affected individuals. Overall, our results highlight the potential of computational tools to elucidate causal mechanisms underlying loss of protein function in loss-of-function variants.

AVAILABILITY AND IMPLEMENTATION

http://mutpred.mutdb.org.

CONTACT

predrag@indiana.edu.

COFACTOR: improved protein function prediction by combining structure, sequence and protein-protein interaction information

The COFACTOR web server is a unified platform for structure-based multiple-level protein function predictions. By structurally threading low-resolution structural models through the BioLiP library, the COFACTOR server infers three categories of protein functions including gene ontology, enzyme commission and ligand-binding sites from various analogous and homologous function templates. Here, we report recent improvements of the COFACTOR server in the development of new pipelines to infer functional insights from sequence profile alignments and protein-protein interaction networks. Large-scale benchmark tests show that the new hybrid COFACTOR approach significantly improves the function annotation accuracy of the former structure-based pipeline and other state-of-the-art functional annotation methods, particularly for targets that have no close homology templates. The updated COFACTOR server and the template libraries are available at http://zhanglab.ccmb.med.umich.edu/COFACTOR/.

IGFN1_v1 is required for myoblast fusion and differentiation

Igfn1 is a complex locus that codes for multiple splicing variants of Immunoglobulin- and Fibronectin-like domain containing proteins predominantly expressed in skeletal muscle. To reveal possible roles for Igfn1, we applied non-selective knock-down by shRNAs as well as specific targeting of Igfn1 exon 13 by CRISPR/Cas9 mutagenesis in C2C12 cells. Decreased expression of Igfn1 variants via shRNAs against the common 3'-UTR region caused a total blunting of myoblast fusion, but did not prevent expression of differentiation markers. Targeting of N-terminal domains by elimination of exon 13 via CRISPR/Cas9 mediated homologous recombination, also resulted in fusion defects as well as large multinucleated cells. Expression of IGFN1_v1 partially rescued fusion and myotube morphology in the Igfn1 exon 13 knock-out cell line, indicating a role for this variant in myoblast fusion and differentiation. However, in vivo overexpression of IGFN1_v1 or the Igfn1 Exon 13 CRISPR/Cas9 targeting vector did not result in significant size changes in transfected fibres.

Effect of follicular dendritic cell secreted protein on gene expression of human periodontal ligament cells

OBJECTIVE

The objective of this study was to investigate the specific roles of follicular dendritic cell secreted protein (FDC-SP), a protein exists in saliva, in the inhibition of calcium precipitation during periodontal regeneration, as well as affect phenotype expression of human periodontal ligament cells (hPDLCs) during the differentiation process.

DESIGN

To investigate this, we applied microarray technology to identify gene expression changes in hPDLCs transfected with FDC-SP and then clustered them according to their biological functions.

RESULTS

One hundred seventy-one genes were found differentially expressed by at least two-fold between FDC-SP -transfected and empty vector-transfected cells. Besides, genes encoding cell-cycle proteins, blood-related and cell differentiation-related proteins tended to be up-regulated after FDC-SP transfection, whereas cytokine/growth factors, signal transduction and metabolism-related genes tended to be down-regulated in hPDLCs overexpression FDC-SP.

CONCLUSIONS

The present study investigated FDC-SP's roles in hPDLCs' phenotype expression, via comparing the gene expression profiles between FDC-SP -transfected hPDLCs and empty vector-transfected cells upon microarray analysis. hPDLCs overexpression FDC-SP appear to display different gene expression patterns. In all, these observations showed a potential of FDC-SP in the maintenance of PDL homeostasis and its ultimate contribution to periodontal would-healing processes.

Arabidopsis Transcription Factors SPL1 and SPL12 Confer Plant Thermotolerance at Reproductive Stage

Plant reproductive organs are vulnerable to heat, but regulation of heat-shock responses in inflorescence is largely uncharacterized. Here, we report that two of the SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) transcriptional factors in Arabidopsis, SPL1 and SPL12, act redundantly in thermotolerance at the reproductive stage. The spl1-1 spl12-1 inflorescences displayed hypersensitivity to heat stress, whereas overexpression of SPL1 or SPL12 enhanced the thermotolerance in both Arabidopsis and tobacco. RNA sequencing revealed 1939 upregulated and 1479 downregulated genes in wild-type inflorescence upon heat stress, among which one-quarter (1,040) was misregulated in spl1-1 spl12-1, indicating that SPL1 and SPL12 contribute greatly to the heat-triggered transcriptional reprogramming in inflorescence. Notably, heat stress induced a large number of abscisic acid (ABA) responsive genes, of which ∼39% were disturbed in heat induction in spl1-1 spl12-1 inflorescence. Preapplication of ABA and overexpression of SPL1 restored the inflorescence thermotolerance in spl1-1 spl12-1 and in the ABA biosynthesis mutant aba2-1, but not in the pyl sextuple mutant defective in ABA receptors PYR1/PYL1/PYL2/PYL4/PYL5/PYL8. Thus, inflorescence thermotolerance conferred by SPL1 and SPL2 involves PYL-mediated ABA signaling. The molecular network consisting of SPL1 and SPL12 illustrated here shed new light on the mechanisms of plant thermotolerance at the reproductive stage.

From Protein Sequence to Protein Function via Multi-Label Linear Discriminant Analysis

Sequence describes the primary structure of a protein, which contains important structural, characteristic, and genetic information and thereby motivates many sequence-based computational approaches to infer protein function. Among them, feature-base approaches attract increased attention because they make prediction from a set of transformed and more biologically meaningful sequence features. However, original features extracted from sequence are usually of high dimensionality and often compromised by irrelevant patterns, therefore dimension reduction is necessary prior to classification for efficient and effective protein function prediction. A protein usually performs several different functions within an organism, which makes protein function prediction a multi-label classification problem. In machine learning, multi-label classification deals with problems where each object may belong to more than one class. As a well-known feature reduction method, linear discriminant analysis (LDA) has been successfully applied in many practical applications. It, however, by nature is designed for single-label classification, in which each object can belong to exactly one class. Because directly applying LDA in multi-label classification causes ambiguity when computing scatters matrices, we apply a new Multi-label Linear Discriminant Analysis (MLDA) approach to address this problem and meanwhile preserve powerful classification capability inherited from classical LDA. We further extend MLDA by l₁-normalization to overcome the problem of over-counting data points with multiple labels. In addition, we incorporate biological network data using Laplacian embedding into our method, and assess the reliability of predicted putative functions. Extensive empirical evaluations demonstrate promising results of our methods.