Extremely thermophilic bacteria of the genus Caldicellulosiruptor utilize carbohydrate components of plant cell walls, including cellulose and hemicellulose, facilitated by a diverse set of glycoside hydrolases (GHs). From a biofuel perspective, this capability is crucial for deconstruction of plant biomass into fermentable sugars. While all species from the genus grow on xylan and acid-pretreated switchgrass, growth on crystalline cellulose is variable. The basis for this variability was examined using microbiological, genomic, and proteomic analyses of eight globally diverse Caldicellulosiruptor species. The open Caldicellulosiruptor pangenome (4,009 open reading frames [ORFs]) encodes 106 GHs, representing 43 GH families, but only 26 GHs from 17 families are included in the core (noncellulosic) genome (1,543 ORFs). Differentiating the strongly cellulolytic Caldicellulosiruptor species from the others is a specific genomic locus that encodes multidomain cellulases from GH families 9 and 48, which are associated with cellulose-binding modules. This locus also encodes a novel adhesin associated with type IV pili, which was identified in the exoproteome bound to crystalline cellulose. Taking into account the core genomes, pangenomes, and individual genomes, the ancestral Caldicellulosiruptor was likely cellulolytic and evolved, in some cases, into species that lost the ability to degrade crystalline cellulose while maintaining the capacity to hydrolyze amorphous cellulose and hemicellulose.

Polo-like kinases play an essential role in the ordered execution of mitotic events and 4 mammalian PLK family members have been identified. Accumulating evidence indicates that PLK1 is an attractive target for anticancer drugs. In this paper, a series of beta-carboline derivatives were synthesized and three compounds, DH281, DH285 and DH287, were identified as potent new PLK inhibitors. We employed various biochemical and cellular approaches to determine the effects of these compounds on the activity of PLK1 and other mitotic kinases and on cell cycle progression. We found that these three compounds could selectively inhibit the kinase activity of purified PLK1, PLK2 and PLK3 in vitro. They show strong antitumor activity against a number of cancer cell lines with relatively low micromolar IC50s, but are relatively less toxic to non-cancer cells (MRC5). Moreover, these compounds could induce obvious accumulation of HeLa cells in G2/M and S phases and trigger apoptosis. Although MRC5 cells show clear S-phase arrest after treatment with these compounds, the G2/M arrest and apoptosis are less insignificant, indicating the distinct sensitivity between normal and cancer cells. We also found that HeLa cells treated with these drugs exhibit monopolar spindles and increased Wee1 protein levels, the characteristics of cells treated with PLK1 inhibitors. Together, these results demonstrate that DH281, DH285 and DH287 beta-carboline compounds are new PLK inhibitors with potential for cancer treatment.

Background

Identification of the novel genes relevant to plant cell-wall (PCW) synthesis represents a highly important and challenging problem. Although substantial efforts have been invested into studying this problem, the vast majority of the PCW related genes remain unknown.

Results

Here we present a computational study focused on identification of the novel PCW genes in Arabidopsis based on the co-expression analyses of transcriptomic data collected under 351 conditions, using a bi-clustering technique. Our analysis identified 217 highly co-expressed gene clusters (modules) under some experimental conditions, each containing at least one gene annotated as PCW related according to the Purdue Cell Wall Gene Families database. These co-expression modules cover 349 known/annotated PCW genes and 2,438 new candidates. For each candidate gene, we annotated the specific PCW synthesis stages in which it is involved and predicted the detailed function. In addition, for the co-expressed genes in each module, we predicted and analyzed their cis regulatory motifs in the promoters using our motif discovery pipeline, providing strong evidence that the genes in each co-expression module are transcriptionally co-regulated. From the all co-expression modules, we infer that 108 modules are related to four major PCW synthesis components, using three complementary methods.

Conclusions

We believe our approach and data presented here will be useful for further identification and characterization of PCW genes. All the predicted PCW genes, co-expression modules, motifs and their annotations are available at a web-based database: http://csbl.bmb.uga.edu/publications/materials/shanwang/CWRPdb/index.html.

The aim of this study was to detect differences in the expression levels of melanoma-associated antigen D4 (MAGED4) mRNA between non-small cell lung cancer (NSCLC) tissues and normal tissues, and to compare differences in the expression levels of MAGED4 in tumor patients. Patients were grouped according to age, gender, smoking history, tumor size, pathological classification, degree of lung cancer cell differentiation and presence of lymph node metastasis. The expression levels of MAGED4 were detected using real-time fluorescence quantitative PCR. MAGED4 expression was higher in squamous cell carcinomas compared to adenocarcinomas (P<0.05), in poorly differentiated tissues compared to well-differentiated tissues (P<0.05), and in patients with lymph node metastasis compared to patients without lymph node metastasis (P<0.05). MAGED4 may be used as a specific antigen for NSCLC to influence the improvement of diagnosis, prognosis and immunological therapy outcomes in lung cancer patients.

Background

Biclustering is a powerful technique for identification of co-expressed gene groups under any (unspecified) substantial subset of given experimental conditions, which can be used for elucidation of transcriptionally co-regulated genes.

Results

We have previously developed a biclustering algorithm, QUBIC, which can solve more general biclustering problems than previous biclustering algorithms. To fully utilize the analysis power the algorithm provides, we have developed a web server, QServer, for prediction, computational validation and analyses of co-expressed gene clusters. Specifically, the QServer has the following capabilities in addition to biclustering by QUBIC: (i) prediction and assessment of conserved cis regulatory motifs in promoter sequences of the predicted co-expressed genes; (ii) functional enrichment analyses of the predicted co-expressed gene clusters using Gene Ontology (GO) terms, and (iii) visualization capabilities in support of interactive biclustering analyses. QServer supports the biclustering and functional analysis for a wide range of organisms, including human, mouse, Arabidopsis, bacteria and archaea, whose underlying genome database will be continuously updated.

Conclusion

We believe that QServer provides an easy-to-use and highly effective platform useful for hypothesis formulation and testing related to transcription co-regulation.

Extracellular matrix metalloproteinase inducer (EMMPRIN) is a transmembrane glycoprotein that is involved in tumor invasion by stimulating matrix metalloproteinase (MMP) expression. Our previous immunohistochemical study found that the expression of EMMPRIN in salivary adenoid cystic carcinoma (SACC) was positively correlated with tumor perineural and perivascular invasion. The present study was designed to further investigate the role of EMMPRIN in the invasion of SACC. Western blot results showed that EMMPRIN was upregulated in the highly metastatic SACC cell line SACC-LM, compared to SACC-83, a SACC cell line with low metastatic ability. Blocking of EMMPRIN by its antibody significantly decreased the adhesion, secretion of MMP-2 and MMP-9, and invasion activity of SACC-LM cells in vitro (P<0.01). Co-cultures of SACC-LM cells with fibroblasts significantly produced elevated levels of MMP-2 and MMP-9, and promoted the in vitro invasion activity of SACC-LM cells, compared with cultures of SACC-LM cells alone (P<0.01). These results indicate that EMMPRIN may play an important role in the invasion of SACC by stimulating the expression of MMP-2 and MMP-9 in tumor and stromal cells.

Objective: In this paper, we investigated the effect of the traditional Chinese medicine Chaiqin Chengqi Decoction (CQCQD) on serum cytokines in acute pancreatitis (AP) patients. Methods: Peripheral blood samples from 107 AP patients were collected within the first 48 h of AP onset and on the 10th day of CQCQD treatment. Control samples were collected from 20 healthy individuals. Serum proinflammatory cytokines tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6), and anti-inflammatory cytokines IL-10 and IL-1β receptor antagonist (IL-1ra) were examined using the Luminex 100 system. Results: Within the first 48 h of AP onset, IL-6 and IL-1ra levels in severe AP (SAP) patients were significantly higher than those in mild AP (MAP) patients, but IL-10 levels in SAP patients were significantly lower than those in MAP patients. Proinflammatory cytokine IL-6 was significantly decreased after CQCQD treatment (P<0.05), especially in SAP patients (n=25 of 36, P<0.05). The hospitalization time of SAP patients was shortened significantly when serum IL-6 decreased after CQCQD treatment (P<0.05). Conclusions: CQCQD decreased proinflammatory cytokine IL-6 levels in AP patients.

Existing methods for orthologous gene mapping suffer from two general problems: (i) they are computationally too slow and their results are difficult to interpret for automated large-scale applications when based on phylogenetic analyses; or (ii) they are too prone to making mistakes in dealing with complex situations involving horizontal gene transfers and gene fusion due to the lack of a sound basis when based on sequence similarity information. We present a novel algorithm, Global Optimization Strategy (GOST), for orthologous gene mapping through combining sequence similarity and contextual (working partners) information, using a combinatorial optimization framework. Genome-scale applications of GOST show substantial improvements over the predictions by three popular sequence similarity-based orthology mapping programs. Our analysis indicates that our algorithm overcomes the intrinsic issues faced by sequence similarity-based methods, when orthology mapping involves gene fusions and horizontal gene transfers. Our program runs as efficiently as the most efficient sequence similarity-based algorithm in the public domain. GOST is freely downloadable at http://csbl.bmb.uga.edu/~maqin/GOST.

We present a new algorithm, BOBRO, for prediction of cis-regulatory motifs in a given set of promoter sequences. The algorithm substantially improves the prediction accuracy and extends the scope of applicability of the existing programs based on two key new ideas: (i) we developed a highly effective method for reliably assessing the possibility for each position in a given promoter to be the (approximate) start of a conserved sequence motif; and (ii) we developed a highly reliable way for recognition of actual motifs from the accidental ones based on the concept of ‘motif closure’. These two key ideas are embedded in a classical framework for motif finding through finding cliques in a graph but have made this framework substantially more sensitive as well as more selective in motif finding in a very noisy background. A comparative analysis shows that the performance coefficient was improved from 29% to 41% by our program compared to the best among other six state-of-the-art prediction tools on a large-scale data sets of promoters from one genome, and also consistently improved by substantial margins on another kind of large-scale data sets of orthologous promoters across multiple genomes. The power of BOBRO in dealing with noisy data was further demonstrated through identification of the motifs of the global transcriptional regulators by running it over 2390 promoter sequences of Escherichia coli K12.

The adsorption of Cd(II) and Pb(II) by squid melanin was investigated. At a metal ion concentration of 2 mM/L, the biosorption efficiency of melanin reached 95% for Cd(II) and Pb(II). The maximum content of bound Cd(II) and Pb(II) was 0.93 mM/g and 0.65 mM/g, respectively. Temperature had no obvious effect on the adsorption of the metals, and in a pH range of 4.0–7.0, the adsorption yield was high and stable. Macrosalts such as NaCl, MgCl2, and CaCl2 had no obvious effect on the binding of Pb(II) but greatly diminished the adsorption of Cd(II), which indicated that different functional groups in squid melanin are responsible for their adsorption. IR analysis of metal ion-enriched squid melanin demonstrated that the possible functional groups responsible for metal binding were phenolic hydroxyl (OH), carboxyl (COOH), and amine groups (NH). This study reports a new material for the removal of heavy metals from low-strength wastewater.

Biclustering extends the traditional clustering techniques by attempting to find (all) subgroups of genes with similar expression patterns under to-be-identified subsets of experimental conditions when applied to gene expression data. Still the real power of this clustering strategy is yet to be fully realized due to the lack of effective and efficient algorithms for reliably solving the general biclustering problem. We report a QUalitative BIClustering algorithm (QUBIC) that can solve the biclustering problem in a more general form, compared to existing algorithms, through employing a combination of qualitative (or semi-quantitative) measures of gene expression data and a combinatorial optimization technique. One key unique feature of the QUBIC algorithm is that it can identify all statistically significant biclusters including biclusters with the so-called ‘scaling patterns’, a problem considered to be rather challenging; another key unique feature is that the algorithm solves such general biclustering problems very efficiently, capable of solving biclustering problems with tens of thousands of genes under up to thousands of conditions in a few minutes of the CPU time on a desktop computer. We have demonstrated a considerably improved biclustering performance by our algorithm compared to the existing algorithms on various benchmark sets and data sets of our own. QUBIC was written in ANSI C and tested using GCC (version 4.1.2) on Linux. Its source code is available at: http://csbl.bmb.uga.edu/∼maqin/bicluster. A server version of QUBIC is also available upon request.