Defining roles for HOX and MEIS1 genes in induction of acute myeloid leukemia

Complex genetic and biochemical interactions between HOX proteins and members of the TALE (i.e., PBX and MEIS) family have been identified in embryonic development, and some of these interactions also appear to be important for leukemic transformation. We have previously shown that HOXA9 collaborates with MEIS1 in the induction of acute myeloid leukemia (AML). In this report, we demonstrate that HOXB3, which is highly divergent from HOXA9, also genetically interacts with MEIS1, but not with PBX1, in generating AML. In addition, we show that the HOXA9 and HOXB3 genes play key roles in establishing all the main characteristics of the leukemias, while MEIS1 functions only to accelerate the onset of the leukemic transformation. Contrasting the reported functional similarities between PREP1 and MEIS1, such as PBX nuclear retention, we also show that PREP1 overexpression is incapable of accelerating the HOXA9-induced AML, suggesting that MEIS1 function in transformation must entail more than PBX nuclear localization. Collectively, these data demonstrate that MEIS1 is a common leukemic collaborator with two structurally and functionally divergent HOX genes and that, in this collaboration, the HOX gene defines the identity of the leukemia.     

Range of HOX/TALE superclass associations and protein domain requirements for HOXA13:MEIS interaction

AbdB-like HOX proteins form DNA-binding complexes with the TALE superclass proteins MEIS1A and MEIS1B, and trimeric complexes have been identified in nuclear extracts that include a second TALE protein, PBX. Thus, soluble DNA-independent protein-protein complexes exist in mammals. The extent of HOX/TALE superclass interactions, protein structural requirements, and sites of in vivo cooperative interaction have not been fully explored. We show that Hoxa13 and Hoxd13 expression does not overlap with that of Meis1-3 in the developing limb; however, coexpression occurs in the developing male and female reproductive tracts (FRTs). We demonstrate that both HOXA13 and HOXD13 associate with MEIS1B in mammalian and yeast cells, and that HOXA13 can interact with all MEIS proteins but not more diverged TALE superclass members. In addition, the C-terminal domains (CTDs) of MEIS1A (18 amino acids) and MEIS1B (93 amino acids) are necessary for HOXA13 interaction; for MEIS1B, this domain was also sufficient. We also show by yeast two-hybrid assay that MEIS proteins can interact with anterior HOX proteins, but for some, additional N-terminal MEIS sequences are required for interaction. Using deletion mutants of HOXA13 and HOXD13, we provide evidence for multiple HOX peptide domains interacting with MEIS proteins. These data suggest that HOX:MEIS interactions may extend to non-AbdB-like HOX proteins in solution and that differences may exist in the MEIS peptide domains utilized by different HOX groups. Finally, the capability of multiple HOX domains to interact with MEIS C-terminal sequences implies greater complexity of the HOX:MEIS protein-protein interactions and a larger role for variation of HOX amino-terminal sequences in specificity of function.     

HOXA9 Modulates Its Oncogenic Partner Meis1 To Influence Normal Hematopoiesis

While investigating the mechanism of action of the HOXA9 protein, we serendipitously identified Meis1 as a HOXA9 regulatory target. Since HOXA9 and MEIS1 play key developmental roles, are cooperating DNA binding proteins and leukemic oncoproteins, and are important for normal hematopoiesis, the regulation of Meis1 by its partner protein is of interest. Loss of Hoxa9 caused downregulation of the Meis1 mRNA and protein, while forced HOXA9 expression upregulated Meis1. Hoxa9 and Meis1 expression was correlated in hematopoietic progenitors and acute leukemias. Meis1^+/− Hoxa9^−/− deficient mice, generated to test HOXA9 regulation of endogenous Meis1, were small and had reduced bone marrow Meis1 mRNA and significant defects in fluorescence-activated cell sorting-enumerated monocytes, mature and pre/pro-B cells, and functional B-cell progenitors. These data indicate that HOXA9 modulates Meis1 during normal murine hematopoiesis. Chromatin immunoprecipitation analysis did not reveal direct binding of HOXA9 to Meis1 promoter/enhancer regions. However, Creb1 and Pknox1, whose protein products have previously been reported to induce Meis1, were shown to be direct targets of HOXA9. Loss of Hoxa9 resulted in a decrease in Creb1 and Pknox1 mRNA, and forced expression of CREB1 in Hoxa9^−/− bone marrow cells increased Meis1 mRNA almost as well as HOXA9, suggesting that CREB1 may mediate HOXA9 modulation of Meis1 expression.While the Hox homeobox genes are widely recognized as important developmental genes (26), we and others have shown that several Hox genes, and Hoxa9 in particular, are important for both normal hematopoiesis (27, 28) and leukemic transformation (25, 29). While the Hoxa9 gene plays a role in embryonic development, much of the research on this gene has focused on its role as an oncogene that is often upregulated in acute myeloid leukemias (12, 29). In an analysis of 6,817 genes, Hoxa9 was the most highly positively correlated with treatment failure in acute myeloid leukemia patients (18). Meis1 is a member of the TALE family of non-Hox homeobox genes, which was initially identified as a frequent viral integration site in myeloid leukemias arising in BXH2 mice (32). The Hoxa9 gene is also upregulated in many of the leukemias arising in the BXH2 animals (33). Forced expression of HOXA9 in murine bone marrow (BM) cells in culture results in immortalization of myeloid progenitor cells (4, 15), while transplantation of HOXA9-infected BM cells results in the eventual induction of acute myelogenous leukemia (25). In contrast, transplantation of BM cells infected with HOXA9 plus MEIS1 results in rapid development of disease (25). Both HOXA9 and MEIS1 are expressed following forced expression of the MLL oncogene (47) or in patients with MLL gene rearrangements (22).Hoxa9 is expressed in numerous tissues during development, including rib (8), limb (17), motor neuron progenitors (10), reproductive tract (9), and mammary gland (7). Hoxa9 is also expressed in normal adult BM (24, 43), and loss of Hoxa9 leads to multiple relatively mild defects in normal hematopoiesis (23, 27, 28). Retroviral expression studies have also shown that HOXA9 and MEIS1 are important for myeloid blood cell differentiation (3, 4). Despite the broad expression of Hoxa9 and other Hox genes, relatively little is known about how the HOX proteins function. An important advance was the discovery that many HOX proteins gain DNA binding specificity by forming complexes with the PBX (6, 31), MEIS1 (41), and PREP1 (2) proteins. Although HOXA9 is capable of binding DNA alone (42), it forms cooperative DNA binding complexes with MEIS1 alone (41) and in a triple complex with PBX proteins (40, 44). Despite these apparent advances, relatively few downstream targets for HOX proteins, and HOXA9 in particular (11), have been confirmed.During ongoing studies of the mechanism of action of the HOXA9 protein, we discovered that HOXA9 appeared to upregulate the Meis1 mRNA and protein. Given the numerous biological connections between HOXA9 and MEIS1, we embarked on studies to explore this pathway. Forced expression of HOXA9 in BM cells upregulated the Meis1 mRNA and protein, while loss of Hoxa9 resulted in a reduction in the Meis1 mRNA and protein. In addition, in a biological model to assess Hoxa9 modulation of Meis1, compound mutant animals that were homozygous null at the Hoxa9 locus and heterozygous at the Meis1 locus showed a significant loss of murine BM monocytes, mature B cells, and pre/pro-B-cell progenitors and an increase in orthochromatophilic erythroblasts in postnatal-day-15 mice compared to results for all controls, suggesting that HOXA9 regulates Meis1 during normal hematopoiesis. Chromatin immunoprecipitation (ChIP) analysis did not show direct binding of HOXA9 to distal or proximal Meis1 genomic regions. However, these studies, together with PCR analysis, showed that HOXA9 binds to and upregulates two genes, Creb1 and Pknox1 (the protein product is subsequently referred to as PREP1), whose protein products have previously been reported to upregulate Meis1 expression (13, 14). Addition of CREB1 to Hoxa9^−/− bone marrow cells increased Meis1 mRNA nearly as effectively as HOXA9. Taken together, our data show that HOXA9 indirectly modulates its DNA binding and oncogenic partner MEIS1 and that the DNA-binding property of HOXA9 is required for this process. We further show that Hoxa9 modulation of Mes1 is biologically important during normal hematopoiesis and that CREB1 may mediate the regulation of Meis1 by HOXA9.     

<Emphasis Type="Italic">Deinococcus radiodurans</Emphasis> RecX and <Emphasis Type="Italic">Escherichia coli</Emphasis> RecX proteins are capable to replace each other in vivo and in vitro

A plasmid carrying the Deinococcus radiodurans recX gene under the control of a lactose promoter decreases the Escherichia coli cell resistance to UV irradiation and γ irradiation and also influences the conjugational recombination process. The D. radiodurans RecX protein functions in the Escherichia coli cells similarly to the E. coli RecX protein. Isolated and purified D. radiodurans RecX and E. coli RecX proteins are able to replace each other interacting with the E. coli RecA and D. radiodurans RecA proteins in vitro. Data obtained demonstrated that regulatory interaction of RecA and RecX proteins preserves a high degree of conservatism despite all the differences in the recombination reparation system between E. coli and D. radiodurans.     

Identifying protein complexes based on density and modularity in protein-protein interaction network

Background

Identifying protein complexes is crucial to understanding principles of cellular organization and functional mechanisms. As many evidences have indicated that the subgraphs with high density or with high modularity in PPI network usually correspond to protein complexes, protein complexes detection methods based on PPI network focused on subgraph's density or its modularity in PPI network. However, dense subgraphs may have low modularity and subgraph with high modularity may have low density, which results that protein complexes may be subgraphs with low modularity or with low density in the PPI network. As the density-based methods are difficult to mine protein complexes with low density, and the modularity-based methods are difficult to mine protein complexes with low modularity, both two methods have limitation for identifying protein complexes with various density and modularity.

Results

To identify protein complexes with various density and modularity, including those have low density but high modularity and those have low modularity but high density, we define a novel subgraph's fitness, f _ρ , as f _ρ = (density) ^ρ *(modularity)^1-ρ, and propose a novel algorithm, named LF_PIN, to identify protein complexes by expanding seed edges to subgraphs with the local maximum fitness value. Experimental results of LF-PIN in S.cerevisiae show that compared with the results of fitness equal to density (ρ = 1) or equal to modularity (ρ = 0), the LF-PIN identifies known protein complexes more effectively when the fitness value is decided by both density and modularity (0<ρ<1). Compared with the results of seven competing protein complex detection methods (CMC, Core-Attachment, CPM, DPClus, HC-PIN, MCL, and NFC) in S.cerevisiae and E.coli, LF-PIN outperforms other seven methods in terms of matching with known complexes and functional enrichment. Moreover, LF-PIN has better performance in identifying protein complexes with low density or with low modularity.

Conclusions

By considering both the density and the modularity, LF-PIN outperforms other protein complexes detection methods that only consider density or modularity, especially in identifying known protein complexes with low density or low modularity.

     

<Emphasis Type="Italic">Sr33</Emphasis> and <Emphasis Type="Italic">Sr35</Emphasis> gene homolog identification in genomes of cereals related to <Emphasis Type="Italic">Aegilops tauschii</Emphasis> and <Emphasis Type="Italic">Triticum monococcum</Emphasis>

Using bioinformatics analysis, the homologs of genes Sr33 and Sr35 were identified in the genomes of Triticum aestivum, Hordeum vulgare, and Triticum urartu. It is known that these genes confer resistance to highly virulent wheat stem rust races (Ug99). To identify amino acid sites important for this resistance, the found homologs were compared with the Sr33 and Sr35 protein sequences. It was found that sequences S5DMA6 and E9P785 are the closest homologs of protein RGAle, a Sr33 gene product, and sequences M7YFA9 (CNL-C) and F2E9R2 are homologs of protein CNL9, a Sr35 gene product. It is assumed that the homologs of genes Sr33 and Sr35, which were obtained from the wild relatives of wheat and barley, can confer resistance to various forms of stem rust and can be used in the future breeding programs aimed at improvement of national wheat varieties.     

Specific features of the protein fraction composition of seeds in plants of the subfamily scilloideae

The composition of protein complexes in seeds was studied in plants of the subfamily Scilloideae. Seed protein contents were compared in 59 species of 12 genera: Scilla L., Hyacinthus L., Bellevalia Lapeyr., Chionodoxa Boiss, Puschkinia Adam., Muscari Mill., Ornithogalum L., Eucomis L’Herit, Galtonia Desne, Velthemia Gleditsch., Hyacinthoides Linn., and Hyacinthella Schur. The results confirmed the heterogeneity of the subfamily: its constituent genera proved to differ in the composition of protein complexes and in the coefficient of evolutionary advancement. The group of salt-soluble proteins dominated by albumins prevailed in seeds of all species studied.     

The mitochondrial DNA of <Emphasis Type="Italic">Dictyostelium discoideum</Emphasis>: complete sequence,gene content and genome organization

We present an overview of the gene content and organization of the mitochondrial genome of Dictyostelium discoideum. The mitochondria genome consists of 55,564?bp with an A + T content of 72.6%. The identified genes include those for two ribosomal RNAs (rnl and rns), 18 tRNAs, ten subunits of the NADH dehydrogenase complex (nad1, 2, 3, 4, 4L, 5, 6, 7, 9 and 11), apocytochrome b (cytb), three subunits of the cytochrome oxidase (cox1/2 and 3), four subunits of the ATP synthase complex (atp1, 6, 8 and 9), 15 ribosomal proteins, and five other ORFs, excluding intronic ORFs. Notable features of D. discoideum mtDNA include the following. (1) All genes are encoded on the same strand of the DNA and a universal genetic code is used. (2) The cox1 gene has no termination codon and is fused to the downstream cox2 gene. The 13 genes for ribosomal proteins and four ORF genes form a cluster 15.4?kb long with several gene overlaps. (3) The number of tRNAs encoded in the genome is not sufficient to support the synthesis of mitochondrial protein. (4) In total, five group I introns reside in rnl and cox1/2, and three of those in cox1/2 contain four free-standing ORFs. We compare the genome to other sequenced mitochondrial genomes, particularly that of Acanthamoeba castellanii.