Mycobacterium tuberculosis Mce1 protein complex initiates rapid induction of transcription of genes involved in substrate trafficking.

The mammalian cell entry (Mce)1 protein complex has an important role during the initial phase of a Mycobacterium tuberculosis (M. tuberculosis) infection. Murine macrophages were infected with M. tuberculosis H37Rv or Δ-mce1 H37Rv, and total RNA was isolated from the host cells at 15, 30 and 60 min, and 4 and 10 h post-infection. With the aim of studying the role for the Mce1 protein complex on host gene expression, the RNA was hybridized onto 44 K whole-genome microarrays. Selected genes were verified by reverse-transcriptase quantitative PCR (RT-QPCR). 'Transport' was the most overrepresented biological process during the first hour post H37Rv infection. Five genes (Abca1 (21.0-fold), Slc16a10 (3.1-fold), Slc6a12 (17.9-fold), Slc6a8 (2.3-fold) and Nr1h3, (5.5-fold)) involved in substrate trafficking were verified by RT-QPCR to be upregulated by >2-fold 1 h post H37Rv infection. By 1 h post Δ-mce1 H37Rv infection, only Abca1 and Slc6a12 were upregulated by >2-fold. A number of other genes, which may be directly involved in substrate trafficking or share the same transcription, were found to have expression profiles similar to the genes involved in substrate trafficking. The Mce1 protein complex has a significant role in the transcriptional activation of genes involved in substrate trafficking during the initial phase of an M. tuberculosis infection.

Integrated genomic profiling of endometrial carcinoma associates aggressive tumors with indicators of PI3 kinase activation.

Although 75% of endometrial cancers are treated at an early stage, 15% to 20% of these recur. We performed an integrated analysis of genome-wide expression and copy-number data for primary endometrial carcinomas with extensive clinical and histopathological data to detect features predictive of recurrent disease. Unsupervised analysis of the expression data distinguished 2 major clusters with strikingly different phenotypes, including significant differences in disease-free survival. To identify possible mechanisms for these differences, we performed a global genomic survey of amplifications, deletions, and loss of heterozygosity, which identified 11 significantly amplified and 13 significantly deleted regions. Amplifications of 3q26.32 harboring the oncogene PIK3CA were associated with poor prognosis and segregated with the aggressive transcriptional cluster. Moreover, samples with PIK3CA amplification carried signatures associated with in vitro activation of PI3 kinase (PI3K), a signature that was shared by aggressive tumors without PIK3CA amplification. Tumors with loss of PTEN expression or PIK3CA overexpression that did not have PIK3CA amplification also shared the PI3K activation signature, high protein expression of the PI3K pathway member STMN1, and an aggressive phenotype in test and validation datasets. However, mutations of PTEN or PIK3CA were not associated with the same expression profile or aggressive phenotype. STMN1 expression had independent prognostic value. The results affirm the utility of systematic characterization of the cancer genome in clinically annotated specimens and suggest the particular importance of the PI3K pathway in patients who have aggressive endometrial cancer.

Insulin detemir is a fully efficacious, low affinity agonist at the insulin receptor.

AIM: To compare the properties of insulin detemir with human insulin or insulin aspart in various in vitro and in vivo experiments, thereby highlighting the importance of performing dose-response studies when investigating insulin analogues, in this study specifically insulin detemir. METHODS: Displacement of membrane-associated insulin receptors from human and rat hepatocytes, and from Chinese Hamster Ovary cells over-expressing human insulin receptor (CHO-hIR) at varying albumin concentrations is measured. Lipogenesis in primary rat adipocytes over time and the effects in the simultaneous presence of insulin detemir and human insulin or insulin aspart are assessed. The hyperinsulinaemic euglycaemic clamp technique in rats is used to establish dose-response curves for multiple metabolic endpoints and to investigate the effects of the simultaneous presence of insulin detemir and human insulin. RESULTS: Both in vitro and in vivo, insulin detemir shows full efficacy and right-shifted parallel dose-response curves compared with human insulin. The potency estimates are different between the in vivo and in vitro conditions and among different in vitro conditions, that is the potency decreases in vitro with increasing albumin concentration. The effects of insulin detemir and human insulin are additive both in vitro and in vivo. CONCLUSIONS: Insulin detemir is fully efficacious compared with human insulin on all metabolic endpoints measured in vitro and in vivo. The fact that the potency estimates are method-dependent emphasizes the importance of establishing full dose-response relationships when characterizing insulin detemir.

Structural fragments in protein model refinement.

We survey a method that uses patterns of residue packing in known protein structures to refine structural models. The method can be used to refine models that include only one coordinate point per residue (C(alpha)) and is not dependent on homology. We demonstrate that the method improves both decoy and CASP7 target models.

The InterPro database, an integrated documentation resource for protein families, domains and functional sites.

Signature databases are vital tools for identifying distant relationships in novel sequences and hence for inferring protein function. InterPro is an integrated documentation resource for protein families, domains and functional sites, which amalgamates the efforts of the PROSITE, PRINTS, Pfam and ProDom database projects. Each InterPro entry includes a functional description, annotation, literature references and links back to the relevant member database(s). Release 2.0 of InterPro (October 2000) contains over 3000 entries, representing families, domains, repeats and sites of post-translational modification encoded by a total of 6804 different regular expressions, profiles, fingerprints and Hidden Markov Models. Each InterPro entry lists all the matches against SWISS-PROT and TrEMBL (more than 1,000,000 hits from 462,500 proteins in SWISS-PROT and TrEMBL). The database is accessible for text- and sequence-based searches at http://www.ebi.ac.uk/interpro/. Questions can be emailed to interhelp@ebi.ac.uk.

Correlations of receptor binding and metabolic and mitogenic potencies of insulin analogs designed for clinical use.

In recent years, analogs of human insulin have been engineered with the aim of improving therapy for people with diabetes. To ensure that the safety profile of the human hormone is not compromised by the molecular modifications, the toxico-pharmacological properties of insulin analogs should be carefully monitored. In this study, we compared the insulin and IGF-I receptor binding properties and metabolic and mitogenic potencies of insulin aspart (B28Asp human insulin), insulin lispro (B28Lys,B29Pro human insulin), insulin glargine (A21Gly,B31Arg,B32Arg human insulin), insulin detemir (NN304) [B29Lys(epsilon-tetradecanoyl), desB30 human insulin], and reference insulin analogs. Receptor affinities were measured using purified human receptors, insulin receptor dissociation rates were determined using Chinese hamster ovary cells overexpressing the human insulin receptor, metabolic potencies were evaluated using primary mouse adipocytes, and mitogenic potencies were determined in human osteosarcoma cells. Metabolic potencies correlated well with insulin receptor affinities. Mitogenic potencies in general correlated better with IGF-I receptor affinities than with insulin receptor off-rates. The 2 rapid-acting insulin analogs aspart and lispro resembled human insulin on all parameters, except for a slightly elevated IGF-I receptor affinity of lispro. In contrast, the 2 long-acting insulin analogs, glargine and detemir, differed significantly from human insulin. The combination of the B31B32diArg and A21Gly substitutions provided insulin glargine with a 6- to 8-fold increased IGF-I receptor affinity and mitogenic potency compared with human insulin. The attachment of a fatty acid chain to LysB29 provided insulin detemir with reduced receptor affinities and metabolic and mitogenic potencies but did not change the balance between mitogenic and metabolic potencies. The safety implications of the increased growth-stimulating potential of insulin glargine are unclear. The reduced in vitro potency of insulin detemir might explain why this analog is not as effective on a molar basis as human insulin in humans.

Searching the protein structure databank with weak sequence patterns and structural constraints.

A method is described in which proteins that match PROSITE patterns are filtered by the root-mean-square deviation of the local 3D structures of the probe and target over the pattern components. This was found to increase the discrimination between true and false members of the protein family but was dependent on how unique the structural features in the pattern were compared to equivalent fragments extracted from the structure databank (for example; if the pattern fell in an alpha-helix, then discrimination was poor.) We then generalised the sequence patterns (by widening the range of amino acid residues allowed at each position) and monitored how well the structural information helped retain specificity. While the discrimination of the pure sequence pattern had generally disappeared at information content values less than ten bits, the discrimination of the combined sequence structure probe remained high at this point before following a similar decay. The displacement between these curves indicates that the structural component is, on average, equivalent to about ten bits. The sequence patterns were also filtered using the structure comparison program SAP, giving a global, rather than local "view" of the proteins. This allowed the information content of the sequence patterns to become even less specific but raised problems of whether some proteins encountered with the same fold but no PROSITE pattern should constitute family members.

Finding flexible patterns in unaligned protein sequences.

We present a new method for the identification of conserved patterns in a set of unaligned related protein sequences. It is able to discover patterns of a quite general form, allowing for both ambiguous positions and for variable length wildcard regions. It allows the user to define a class of patterns (e.g., the degree of ambiguity allowed and the length and number of gaps), and the method is then guaranteed to find the conserved patterns in this class scoring highest according to a significance measure defined. Identified patterns may be refined using one of two new algorithms. We present a new (nonstatistical) significance measure for flexible patterns. The method is shown to recover known motifs for PROSITE families and is also applied to some recently described families from the literature.

Structure comparison and structure patterns.

This article investigates aspects of pairwise and multiple structure comparison, and the problem of automatically discover common patterns in a set of structures. Descriptions and representation of structures and patterns are described, as well as scoring and algorithms for comparison and discovery. A framework and nomenclature is developed for classifying different methods, and many of these are reviewed and placed into this framework.

Approaches to the automatic discovery of patterns in biosequences.

This paper surveys approaches to the discovery of patterns in biosequences and places these approaches within a formal framework that systematises the types of patterns and the discovery algorithms. Patterns with expressive power in the class of regular languages are considered, and a classification of pattern languages in this class is developed, covering the patterns that are the most frequently used in molecular bioinformatics. A formulation is given of the problem of the automatic discovery of such patterns from a set of sequences, and an analysis is presented of the ways in which an assessment can be made of the significance of the discovered patterns. It is shown that the problem is related to problems studied in the field of machine learning. The major part of this paper comprises a review of a number of existing methods developed to solve the problem and how these relate to each other, focusing on the algorithms underlying the approaches. A comparison is given of the algorithms, and examples are given of patterns that have been discovered using the different methods.

Effect of fatty acids and selected drugs on the albumin binding of a long-acting, acylated insulin analogue.

NN304 (LysB29-tetradecanoyl, des(B30)-insulin) is a new soluble, long-acting insulin analogue that is tightly bound to human serum albumin differentiating it from human insulin. In the present study, we investigate the effect of fatty acids and selected drugs on the binding of NN304 to human serum albumin in vitro. Binding of the first fatty acid equivalent to albumin does not affect the binding of NN304. None of the tested drugs compete with the binding of NN304 at drug-to-albumin concentration ratios of < 1. The binding of NN304 is shown to be independent of binding of drugs in the two major binding pockets that are located in domains IIA and IIIA of the albumin molecule. Tolbutamide and glibenclamide do not compete with NN304 for binding to albumin at therapeutic drug-to-albumin concentration ratios. High concentrations of acetylsalicylic acid and ibuprofen decrease the affinity of NN304 for albumin, but these interactions occur at drug-to-albumin concentration ratios that are higher than clinically relevant. In conclusion, NN304 is unlikely to be involved in clinically significant drug interactions at the albumin binding level. The unique ligand binding properties of serum albumin and its abundance in the extracellular fluids makes fatty acid acylation and albumin binding an attractive protraction principle for insulin and potentially also for other peptide drugs.

Albumin binding and time action of acylated insulins in various species.

Insulins acylated with fatty acids at the epsilon-amino group of LysB29 constitute a new class of insulin analogs, which are prolonged-acting due to albumin binding. In the present study it is shown that the affinity of fatty acid acylated insulins for albumin varies considerably (> 50-fold) among species. The relative affinities of acylated insulin for albumin in human, pig, and rabbit serum are about 1:1:5:35. The several fold higher binding affinity in rabbit serum than in pig serum is reflected in a relatively more protracted effect after sc injection in rabbits than in pigs. Due to the similar binding affinities in pig serum and human serum, the pig model should provide a useful estimate of the degree of protraction of acylated insulin in humans. The results emphasize that species differences in ligand binding can be of major importance in the preclinical evaluation of highly albumin bound drugs.

Specific cellular signal-transduction responses to in vivo combination therapy with ATRA, valproic acid and theophylline in acute myeloid leukemia.

Acute myeloid leukemia (AML) frequently comprises mutations in genes that cause perturbation in intracellular signaling pathways, thereby altering normal responses to growth factors and cytokines. Such oncogenic cellular signal transduction may be therapeutic if targeted directly or through epigenetic regulation. We treated 24 selected elderly AML patients with all-trans retinoic acid for 2 days before adding theophylline and the histone deacetylase inhibitor valproic acid (ClinicalTrials.gov NCT00175812; EudraCT no. 2004-001663-22), and sampled 11 patients for peripheral blood at day 0, 2 and 7 for single-cell analysis of basal level and signal-transduction responses to relevant myeloid growth factors (granulocyte-colony-stimulating factor, granulocyte/macrophage-colony-stimulating factor, interleukin-3, Flt3L, stem cell factor, erythropoietin, CXCL-12) on 10 signaling molecules (CREB, STAT1/3/5, p38, Erk1/2, Akt, c-Cbl, ZAP70/Syk and rpS6). Pretreatment analysis by unsupervised clustering and principal component analysis divided the patients into three distinguishable signaling clusters (non-potentiated, potentiated basal and potentiated signaling). Signal-transduction pathways were modulated during therapy and patients moved between the clusters. Patients with multiple leukemic clones demonstrated distinct stimulation responses and therapy-induced modulation. Individual signaling profiles together with clinical and hematological information may be used to early identify AML patients in whom epigenetic and signal-transduction targeted therapy is beneficial.

Efficient discovery of conserved patterns using a pattern graph.

MOTIVATION: We have previously reported an algorithm for discovering patterns conserved in sets of related unaligned protein sequences. The algorithm was implemented in a program called Pratt. Pratt allows the user to define a class of patterns (e.g. the degree of ambiguity allowed and the length and number of gaps), and is then guaranteed to find the conserved patterns in this class scoring highest according to a defined fitness measure. In many cases, this version of Pratt was very efficient, but in other cases it was too time consuming to be applied. Hence, a more efficient algorithm was needed. RESULTS: In this paper, we describe a new and improved searching strategy that has two main advantages over the old strategy. First, it allows for easier integration with programs for multiple sequence alignment and data base search. Secondly, it makes it possible to use branch-and-bound search, and heuristics, to speed up the search. The new search strategy has been implemented in a new version of the Pratt program.

J-Express: exploring gene expression data using Java.

J-Express is a Java application that allows the user to analyze gene expression (microarray) data in a flexible way giving access to multidimensional scaling, clustering, and visualization methods in an integrated manner. Specifically, J-Express includes implementations of hierarchical clustering, k-means, principal component analysis, and self-organizing maps. At present, it does not include methods for comparing two or more experiments for differentially expressed genes. The application is completely portable and requires only that a Java runtime environment 1.2 is installed on the system. Its efficiency allows interactive clustering of thousands of expression profiles on standard personal computers.

Discovering patterns and subfamilies in biosequences.

We consider the problem of automatic discovery of patterns and the corresponding subfamilies in a set of biosequences. The sequences are unaligned and may contain noise of unknown level. The patterns are of the type used in PROSITE database. In our approach we discover patterns and the respective subfamilies simultaneously. We develop a theoretically substantiated significance measure for a set of such patterns and an algorithm approximating the best pattern set and the subfamilies. The approach is based on the minimum description length (MDL) principle. We report a computing experiment correctly finding subfamilies in the family of chromo domains and revealing new strong patterns.

Predicting gene regulatory elements in silico on a genomic scale.

We performed a systematic analysis of gene upstream regions in the yeast genome for occurrences of regular expression-type patterns with the goal of identifying potential regulatory elements. To achieve this goal, we have developed a new sequence pattern discovery algorithm that searches exhaustively for a priori unknown regular expression-type patterns that are over-represented in a given set of sequences. We applied the algorithm in two cases, (1) discovery of patterns in the complete set of >6000 sequences taken upstream of the putative yeast genes and (2) discovery of patterns in the regions upstream of the genes with similar expression profiles. In the first case, we looked for patterns that occur more frequently in the gene upstream regions than in the genome overall. In the second case, first we clustered the upstream regions of all the genes by similarity of their expression profiles on the basis of publicly available gene expression data and then looked for sequence patterns that are over-represented in each cluster. In both cases we considered each pattern that occurred at least in some minimum number of sequences, and rated them on the basis of their over-representation. Among the highest rating patterns, most have matches to substrings in known yeast transcription factor-binding sites. Moreover, several of them are known to be relevant to the expression of the genes from the respective clusters. Experiments on simulated data show that the majority of the discovered patterns are not expected to occur by chance.

Discovery of local packing motifs in protein structures.

We present a language for describing structural patterns of residues in protein structures and a method for the discovery of such patterns that recur in a set of protein structures. The patterns impose restrictions on the spatial position of each residue, their order along the amino acid chain, and which amino acids are allowed in each position. Unlike other methods for comparing sets of protein structures, our method is not based on the use of pairwise structure comparisons which is often time consuming and can produce inconsistent results. Instead, the method simultaneously takes into account information from all structures in the search for conserved structure patterns which are potential structure motifs. The method is based on describing the spatial neighborhoods of each residue in each structure as a string and applying a sequence pattern discovery method to find patterns common to subsets of these strings. Finally it is checked whether the similarities between the neighborhood strings correspond to spatially similar substructures. We apply the method to analyze sets of very disparate proteins from the four different protein families: serine proteases, cuprodoxins, cysteine proteinases, and ferredoxins. The motifs found by the method correspond well to the site and motif information given in the annotation of these proteins in PDB, Swiss-Prot, and PROSITE. Furthermore, the motifs are confirmed by using the motif data to constrain the structural alignment of the proteins obtained with the program SAP. This gave the best superposition/alignment of the proteins given the motif assignment.