Articles de revues sur le sujet « RRM, RNA binding Proteins, MSI-1 »

Abstract RNA-binding proteins (RBPs) play critical roles in cell homeostasis by controlling gene expression post-transcriptionally, contributing to mRNA processing events (splicing, polyadenylation, localization, stability, export and translation). The involvement of RBPs to tumorigenesis, through genetic perturbation or epigenetic dysregulation, has been found in a variety of human cancers. The RBP MUSASHI-2 (MSI2) contributes to the pathogenesis of a spectrum of solid tumors and hematologic malignancies and predicts a worse clinical outcome in patients with myeloid and acute lymphoblastic leukemia (MDS, AML and ALL). Thus, MSI2 has been proposed as a putative biomarker for diagnosis as well as a potential therapeutic target for AML. However, there are currently no specific inhibitors for MSI. Previous work from our lab reported a Fluorescent Polarization (FP) screen with 6,208 compounds identifying small-molecules with MSI RNA-binding inhibition activity. Here, we characterize Ro 08-2750 (Ro), best FP screen hit, as a MSI RNA-competitive inhibitor. Electrophoresis Mobility Shift Assays (EMSA) demonstrated Ro inhibition of MSI2-RNA complexes formation. MicroScale Thermophoresis (MST) interaction studies showed that the compound interacts with MSI2 full-length and RNA-Recognition Motif 1 (RRM1) with μM affinity and with nearly 20-fold lower KD to an RBP control (SYNCRIP). We obtained the crystal structure of MSI2 RRM1 at 1.7Å and docking and mutagenesis validation confirmed K22, F66, F97 and R100 as crucial binding residues in the RNA-binding pocket. To further prove structure activity relationship, we used two chemical analogs: Ro-OH, an alcohol derivative of the Ro's aldehyde, showed 10-fold reduced activity and Ro-NGF, containing the Ro isoalloxazine scaffold, showed no binding or activity in vitro. Of note, in proliferation assays Ro EC50 was 2.6±0.1 μM in MLL-AF9 bone marrow cells and an average of 8.4±1.1 μM in MOLM13 and K562 human AML cells, whereas RoOH and RoNGF showed 10-fold or >50 μM EC50, respectively. Ro significantly reduced binding of MSI2 to its mRNA targets (such as cMYC, CDKN1A or SMAD3) in an RNA-IP and a direct effect in their protein translation in human leukemia cells. RNA-sequencing of 4h Ro treated MOLM13 and K562 AML cells resulted in gene expression changes that enriched for the gene expression profiling after shRNA mediated depletion of MSI2 in CML-BC and AML cell lines. Ro demonstrated a significant therapeutic index abolishing MLL-AF9+ BM colony formation at concentrations that did not affect the plating efficiency of normal Lin-Sca+cKit+ (LSK) cells. Similarly, Ro demonstrated differential sensitivity in three AML patient samples colony formation compared to normal human CD34+ cord blood cells. Finally, we sought to determine Ro in vivo activity by using an aggressive murine MLL-AF9 murine leukemia model. Acute treatment (4h and 12hr) with 13.75 mg/kg Ro in DMSO reduced c-KIT protein abundance and intracellular c-MYC. Administration of the same Ro dose every 3 days was well tolerated and showed a significant reduction in spleen weights, white blood cell counts and c-MYC levels compared to the controls. These data provide the feasibility that targeting MSI in vivo could have therapeutic efficacy in AML. This study identifies and characterizes Ro 08-2750 as a compound selectively inhibiting the oncogenic RNA-binding activity of MSI in myeloid leukemia. Ro targeting an RRM motif to block RNA activity represents a valuable proof of concept for the general inhibition of these class of RNA regulators. Overall, we provide a framework to identify and test novel RBP inhibitors thus validating this class of proteins as chemically "druggable" novel therapeutic targets in cancer. Disclosures Chodera: Schrödinger: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Proteins with RNA recognition motifs (RRMs) have important roles in a great many aspects of RNA metabolism. However, this family has yet to be systematically studied in any single organism. In order to investigate the size of the RRM gene family in Drosophila melanogaster and to clone members of this family, we used a polymerase chain reaction (PCR) with highly degenerate oligonucleotides to amplify DNA fragments between the RNP-1 and RNP-2 consensus sequences of the RRM proteins. Cloning and sequencing of 124 PCR products revealed 12 different RRM sequences (RRM1 to RRM12). When PCR products were used as probes in genomic Southern and Northern (RNA) analyses, 16 restriction fragments and 25 transcripts, respectively, were detected. Since the combinations of nucleotide sequences represented in the PCR primers correspond to only 4% of the RRM sequences inferred to be possible from known RRM sequences, we estimate the size of the RRM gene family in the order of three hundred genes in flies. In order to gain insight into the possible functions of the genes encoding the RRMs, we analyzed the sequence similarities between the 12 RRMs and 62 RRM sequences of known proteins. This analysis showed that the RRMs of functionally related proteins have similar sequences and are clustered together in the RRM gene tree. On the basis of this observation, the RRMs can be divided into three groups: a heterogeneous nuclear ribonucleoprotein type, a splicing regulator type, and a development-specific factor type. This result suggests that we have isolated good candidates for both housekeeping and developmentally important genes involved in RNA metabolism.

Proteins with RNA recognition motifs (RRMs) have important roles in a great many aspects of RNA metabolism. However, this family has yet to be systematically studied in any single organism. In order to investigate the size of the RRM gene family in Drosophila melanogaster and to clone members of this family, we used a polymerase chain reaction (PCR) with highly degenerate oligonucleotides to amplify DNA fragments between the RNP-1 and RNP-2 consensus sequences of the RRM proteins. Cloning and sequencing of 124 PCR products revealed 12 different RRM sequences (RRM1 to RRM12). When PCR products were used as probes in genomic Southern and Northern (RNA) analyses, 16 restriction fragments and 25 transcripts, respectively, were detected. Since the combinations of nucleotide sequences represented in the PCR primers correspond to only 4% of the RRM sequences inferred to be possible from known RRM sequences, we estimate the size of the RRM gene family in the order of three hundred genes in flies. In order to gain insight into the possible functions of the genes encoding the RRMs, we analyzed the sequence similarities between the 12 RRMs and 62 RRM sequences of known proteins. This analysis showed that the RRMs of functionally related proteins have similar sequences and are clustered together in the RRM gene tree. On the basis of this observation, the RRMs can be divided into three groups: a heterogeneous nuclear ribonucleoprotein type, a splicing regulator type, and a development-specific factor type. This result suggests that we have isolated good candidates for both housekeeping and developmentally important genes involved in RNA metabolism.

ABSTRACT To understand the regulation of cap-dependent translation initiation mediated by specific 5′ untranslated region (UTR) RNA-protein interactions in mammalian cells, we have studied the selective translation of influenza virus mRNAs. Previous work has shown that the host cell mRNA binding protein guanine-rich sequence factor 1 (GRSF-1) bound specifically to conserved viral 5′ UTR sequences and stimulated translation of viral 5′ UTR-driven mRNAs in vitro. In the present study, we have characterized the functional domains of GRSF-1 and mapped the RNA binding activity of GRSF-1 to RRM 2 (amino acids 194 to 275) with amino-terminal deletion glutathione S-transferase (GST)-GRSF-1 proteins. When these mutants were assayed for functional activity in vitro, deletion of an Ala-rich region (Δ[2-94]) appeared to diminish translational stimulation, while deletion of the Ala-rich region in addition to RRM 1 (Δ[2-194]) resulted in a 4-fold increase in translational activation over wild-type GRSF-1 (an overall 20-fold increase in activity). We have also mapped the GRSF-1 RNA binding site on influenza virus NP and NS1 5′ UTRs, which was determined to be the sequence AGGGU. With polysome fractionation and cDNA microarray analysis, we have identified cellular and viral mRNAs containing putative GRSF-1 binding sites that were transcriptionally up-regulated and selectively recruited to polyribosomes following influenza virus infection. Taken together, these studies demonstrate that RRM 2 is critical for GRSF-1 RNA binding and translational activity. Further, our data suggest GRSF-1 functions by selectively recruiting cellular and viral mRNAs containing 5′ UTR GRSF-1 binding sites to polyribosomes, which is mediated through interactions with cellular proteins.

U2AF65 (U2AF2) and PUF60 (PUF60) are splicing factors important for recruitment of the U2 small nuclear ribonucleoprotein to lariat branch points and selection of 3′ splice sites (3′ss). Both proteins preferentially bind uridine-rich sequences upstream of 3′ss via their RNA recognition motifs (RRMs). Here, we examined 36 RRM substitutions reported in cancer patients to identify variants that alter 3′ss selection, RNA binding and protein properties. Employing PUF60- and U2AF65-dependent 3′ss previously identified by RNA-seq of depleted cells, we found that 43% (10/23) and 15% (2/13) of independent RRM mutations in U2AF65 and PUF60, respectively, conferred splicing defects. At least three RRM mutations increased skipping of internal U2AF2 (~9%, 2/23) or PUF60 (~8%, 1/13) exons, indicating that cancer-associated RRM mutations can have both cis- and trans-acting effects on splicing. We also report residues required for correct folding/stability of each protein and map functional RRM substitutions on to existing high-resolution structures of U2AF65 and PUF60. These results identify new RRM residues critical for 3′ss selection and provide relatively simple tools to detect clonal RRM mutations that enhance the mRNA isoform diversity.

AU-rich element binding/degradation factor 1 (AUF1) plays a role in destabilizing mRNAs by forming complexes with AU-rich elements (ARE) in the 3′-untranslated regions. Multiple AUF1-ARE complexes regulate the translation of encoded products related to the cell cycle, apoptosis, and inflammation. AUF1 contains two tandem RNA recognition motifs (RRM) and a Gln- (Q-) rich domain in their C-terminal region. To observe how the two RRMs are involved in recognizing ARE, we obtained the AUF1-p37 protein covering the two RRMs. However, only N-terminal RRM (RRM1) was crystallized and its structure was determined at 1.7 Å resolution. It appears that the RRM1 and RRM2 separated before crystallization. To demonstrate which factors affect the separate RRM1-2, we performed limited proteolysis using trypsin. The results indicated that the intact proteins were cleaved by unknown proteases that were associated with them prior to crystallization. In comparison with each of the monomers, the conformations of theβ2-β3 loops were highly variable. Furthermore, a comparison with the RRM1-2 structures of HuR and hnRNP A1 revealed that a dimer of RRM1 could be one of the possible conformations of RRM1-2. Our data may provide a guidance for further structural investigations of AUF1 tandem RRM repeat and its mode of ARE binding.

ABSTRACT It was reported previously that four baby hamster kidney (BHK) proteins with molecular masses of 108, 60, 50, and 42 kDa bind specifically to the 3′-terminal stem-loop of the West Nile virus minus-stand RNA [WNV 3′(−) SL RNA] (P. Y. Shi, W. Li, and M. A. Brinton, J. Virol. 70:6278-6287, 1996). In this study, p42 was purified using an RNA affinity column and identified as TIAR by peptide sequencing. A 42-kDa UV-cross-linked viral RNA-cell protein complex formed in BHK cytoplasmic extracts incubated with the WNV 3′(−) SL RNA was immunoprecipitated by anti-TIAR antibody. Both TIAR and the closely related protein TIA-1 are members of the RNA recognition motif (RRM) family of RNA binding proteins. TIA-1 also binds to the WNV 3′(−) SL RNA. The specificity of these viral RNA-cell protein interactions was demonstrated using recombinant proteins in competition gel mobility shift assays. The binding site for the WNV 3′(−) SL RNA was mapped to RRM2 on both TIAR and TIA-1. However, the dissociation constant (Kd ) for the interaction between TIAR RRM2 and the WNV 3′(−) SL RNA was 1.5 × 10−8, while that for TIA-1 RRM2 was 1.12 × 10−7. WNV growth was less efficient in murine TIAR knockout cell lines than in control cells. This effect was not observed for two other types of RNA viruses or two types of DNA viruses. Reconstitution of the TIAR knockout cells with TIAR increased the efficiency of WNV growth, but neither the level of TIAR nor WNV replication was as high as in control cells. These data suggest a functional role for TIAR and possibly also for TIA-1 during WNV replication.

Abstract We have performed a genetic analysis of the 14C region of the X chromosome of Drosophila melanogaster to isolate loss of function alleles of no-on-transient A (nonA; 14C1-2; 1-52.3). NONA is a nuclear protein common to many cell types, which is present in many puffs on polytene chromosomes. Sequence data suggest that the protein contains a pair of RNA binding motifs (RRM) found in many single-strand nucleic acid binding proteins. Hypomorphic alleles of this gene, which lead to aberrant visual and courtship song behavior, still contain normally distributed nonA RNA and NONA protein in embryos, and in all available alleles NONA protein is present in puffs of third instar larval polytene chromosomes. We find that complete loss of this general nuclear protein is semilethal in hemizygous males and homozygous cell lethal in the female germline. Surviving males show more extreme defects in nervous system function than have been described for the hypomorphic alleles. Five other essential genes that reside within this region have been partially characterized.

Background: Methylation of carbon-5 of cytosines (m5C) is a conserved post-transcriptional nucleotide modification of RNA with widespread distribution across organisms. It can be further modified to yield 5-hydroxymethylcytidine (hm5C), 5-formylcytidine (f5C), 2´-O-methyl-5-hydroxymethylcytidine (hm5Cm) and 2´-O-methyl-5-formylcytidine (f5Cm). How m5C, and specially its derivates, contribute to biology mechanistically is poorly understood. We recently showed that m5C is required for Caenorhabditis elegans development and fertility under heat stress. m5C has been shown to participate in mRNA transport and maintain mRNA stability through its recognition by the reader proteins ALYREF and YBX1, respectively. Hence, identifying readers for RNA modifications can enhance our understanding in the biological roles of these modifications. Methods: To contribute to the understanding of how m5C and its oxidative derivatives mediate their functions, we developed RNA baits bearing modified cytosines in diverse structural contexts to pulldown potential readers in C. elegans. Potential readers were identified using mass spectrometry. The interaction of two of the putative readers with m5C was validated using immunoblotting. Results: Our mass spectrometry analyses revealed unique binding proteins for each of the modifications. In silico analysis for phenotype enrichments suggested that hm5Cm unique readers are enriched in proteins involved in RNA processing, while readers for m5C, hm5C and f5C are involved in germline processes. We validated our dataset by demonstrating that the nematode ALYREF homologues ALY-1 and ALY-2 preferentially bind m5C in vitro. Finally, sequence alignment analysis showed that several of the putative m5C readers contain the conserved RNA recognition motif (RRM), including ALY-1 and ALY-2. Conclusions: The dataset presented here serves as an important scientific resource that will support the discovery of new functions of m5C and its derivatives. Furthermore, we demonstrate that ALY-1 and ALY-2 bind to m5C in C. elegans.

Splicing generates many mRNA strands from a single precursor mRNA, expanding the proteome and enhancing intracellular diversity. Both initial assembly and activation of the spliceosome require an essential family of splicing factors called serine-arginine (SR) proteins. Protein phosphatase 1 (PP1) regulates the SR proteins by controlling phosphorylation of a C-terminal arginine-serine–rich (RS) domain. These modifications are vital for the subcellular localization and mRNA splicing function of the SR protein. Although PP1 has been shown to dephosphorylate the prototype SR protein splicing factor 1 (SRSF1), the molecular nature of this interaction is not understood. Here, using NMR spectroscopy, we identified two electrostatic residues in helix α2 and a hydrophobic residue in helix α1 in the RNA recognition motif 1 (RRM1) of SRSF1 that constitute a binding surface for PP1. Substitution of these residues dissociated SRSF1 from PP1 and enhanced phosphatase activity, reducing phosphorylation in the RS domain. These effects lead to shifts in alternative splicing patterns that parallel increases in SRSF1 diffusion from speckles to the nucleoplasm brought on by regiospecific decreases in RS domain phosphorylation. Overall, these findings establish a molecular and biological connection between PP1-targeted amino acids in an RRM with the phosphorylation state and mRNA-processing function of an SR protein.

RNA-binding protein 39 (RBM39) is a splicing factor and a transcriptional co-activator of estrogen receptors and Jun/AP-1, and its function has been associated with malignant progression in a number of cancers. The C-terminal RRM domain of RBM39 belongs to the U2AF homology motif family (UHM), which mediate protein–protein interactions through a short tryptophan-containing peptide known as the UHM-ligand motif (ULM). Here, crystal and solution NMR structures of the RBM39-UHM domain, and the crystal structure of its complex with U2AF65-ULM, are reported. The RBM39–U2AF65 interaction was confirmed by co-immunoprecipitation from human cell extracts, by isothermal titration calorimetry and by NMR chemical shift perturbation experiments with the purified proteins. When compared with related complexes, such as U2AF35–U2AF65 and RBM39–SF3b155, the RBM39-UHM–U2AF65-ULM complex reveals both common and discriminating recognition elements in the UHM–ULM binding interface, providing a rationale for the known specificity of UHM–ULM interactions. This study therefore establishes a structural basis for specific UHM–ULM interactions by splicing factors such as U2AF35, U2AF65, RBM39 and SF3b155, and a platform for continued studies of intermolecular interactions governing disease-related alternative splicing in eukaryotic cells.

Follicular development and oocyte maturation in mammals requires the temporal and spatial control of protein production. Consequently, it is hypothesised that the preovulatory follicle represses mRNA translation until specific proteins are required during oocyte maturation. Increasingly RNA-binding proteins are being recognised as important contributors to germ cell development, particularly during oocyte transcriptional quiescence. We have identified the presence of RNA-binding protein musashi-1 (Msi-1) mRNA within the mouse ovary and mature mouse oocyte, where the protein is believed to act as a translational repressor by binding to specific sequences within the 3' UTR of target mRNA molecules. Recent studies in various mammalian systems have identified p21 WAF1, cdkn2a, notch and m-numb as potential targets of Msi-1. We have also identified morf4l1 as a potential target through preliminary pulldown and microarray analysis using a GST tagged Msi-1 recombinant protein. To further study these potential targets, a transgenic Msi-1 mouse was produced to overexpress the RNA-binding protein in the developing oocyte. Real time PCR, performed on intact ovaries of WT and Tg mice, has so far demonstrated a 1.5-fold increase in Msi-1 expression in tgMsi-1/+ ovaries, above WT ovary expression. Real time PCR analysis of Msi-1 target mRNA expression has also shown an overall increase in expression in the tgMsi-1/+ ovaries of p21 WAF1 (~2.5-fold), cdkn2a (~2-fold), and notch (~3-fold). However m-numb and morf4l1 do not appear to be targets of Msi-1 in the oocyte, with no significant difference in expression between the WT and tgMsi-1/+ ovaries analysed. Functional quantification of oocyte development reveals a significantly less oocytes produced from superovulated juvenile mice compared with wild type litter mates. Therefore, preliminary analysis suggests that Msi-1 may play a role in binding the transcripts of genes necessary for cell cycle regulation and chromatin remodelling, characteristic of meiotic progression and oocyte development.

The therapeutic potential of Musashi (MSI) RNA-binding proteins, important stemness-associated gene expression regulators, remains insufficiently understood in breast cancer. This study identifies the interplay between MSI protein expression, stem cell characteristics, radioresistance, cell invasiveness and migration. MSI-1, MSI-2 and Notch pathway elements were investigated via quantitative polymerase chain reaction (qPCR) in 19 triple-negative breast cancer samples. Measurements were repeated in MDA-MB-231 cells after MSI-1 and -2 siRNA-mediated double knockdown, with further experiments performed after MSI silencing. Flow cytometry helped quantify expression of CD44 and leukemia inhibitory factor receptor (LIFR), changes in apoptosis and cell cycle progression. Proliferation and irradiation-induced effects were assessed using colony formation assays. Radiation-related proteins were investigated via Western blots. Finally, cell invasion assays and digital holographic microscopy for cell migration were performed. MSI proteins showed strong correlations with Notch pathway elements. MSI knockdown resulted in reduction of stem cell marker expression, cell cycle progression and proliferation, while increasing apoptosis. Cells were radiosensitized as radioresistance-conferring proteins were downregulated. However, MSI-silencing-mediated LIFR downregulation resulted in enhanced cell invasion and migration. We conclude that, while MSI knockdown results in several therapeutically desirable consequences, enhanced invasion and migration need to be counteracted before knockdown advantages can be fully exploited.

In ovarian cancer, therapy resistance mechanisms complicate cancer cell eradication. Targeting Musashi RNA-binding proteins (MSI) may increase therapeutic efficacy. Database analyses were performed to identify gene expression associations between MSI proteins and key therapy resistance and cancer stem cell (CSC) genes. Then, ovarian cancer cells were subjected to siRNA-based dual knockdown of MSI-1 and MSI-2. CSC and cell cycle gene expression was investigated using quantitative polymerase chain reaction (qPCR), western blots, and flow cytometry. Metabolic activity and chemoresistance were assessed by MTT assay. Clonogenic assays were used to quantify cell survival post-irradiation. Database analyses demonstrated positive associations between MSI proteins and putative CSC markers NOTCH, MYC, and ALDH4A1 and negative associations with NOTCH inhibitor NUMB. MSI-2 expression was negatively associated with the apoptosis regulator p21. MSI-1 and MSI-2 were positively correlated, informing subsequent dual knockdown experiments. After MSI silencing, CSC genes were downregulated, while cell cycle progression was reduced. Metabolic activity was decreased in some cancer cells. Both chemo- and radioresistance were reduced after dual knockdown, suggesting therapeutic potential. Dual knockdown of MSI proteins is a promising venue to impede tumor growth and sensitize ovarian cancer cells to irradiation and chemotherapy.

Control of the maternal mRNA pool during oocyte maturation is crucial to the correct temporal and spatial expression of proteins, particularly during oocyte transcriptional quiescence. We have identified Musashi-1 as being present within the oocyte/ovary, where this RNA-binding protein is believed to act as a translational repressor of target mRNAs. Recent studies in mammalian neural and intestinal systems have identified a number of cell cycle regulators as potential targets of Msi-1. Using Msi-1 protein-RNA immunoprecipitation, we have also identified musashi-2 (msi-2) and c-mos as putative targets in the mouse oocyte. To further study these targets, a transgenic mouse was produced to overexpress Msi-1 exclusively in the oocyte. QPCR analysis, performed on intact ovaries of wild type (WT) and Tg mice, confirmed a 1.5-fold increase in msi-1 expression in tgMsi-1/+ ovaries in excess of WT ovary expression. QPCR analysis of Msi-1 target expression, performed on intact WT and Tg ovaries, in conjunction with transcript obtained from the Msi-1 protein-RNA immunoprecipitation, revealed an overall increase in expression in the tgMsi-1/+ and Msi-1 IP samples, respectively, of p21WAF-1 (~2.5-fold; undetected), cdkn2a (~2-fold; undetected), notch1 (~3-fold;undetected), c-mos (no difference; ~41-fold) and msi-2 (~7-fold; ~10-fold). Immunohistochemical analysis of Msi-2 protein expression in transgenic juvenile mouse ovaries,demonstrated a decrease in expression of Msi-2 in tgMsi-1/+ ovaries, when compared to WT ovary expression, suggesting that Msi-2 mRNA is translationally repressed by Msi-1. Therefore, preliminary analysis suggests that Msi-1 may play a role inregulating transcripts of genes necessary for processes characteristic of meiotic progression and oocyte development.

The Musashi family of RNA-binding proteins controls several biological processes including stem cell maintenance, cell division and neural function. Previously, we demonstrated that the C. elegans Musashi ortholog, msi-1, regulates forgetting via translational repression of the Arp2/3 actin-branching complex. However, the mechanisms controlling MSI-1 activity during the regulation of forgetting are currently unknown. Here we investigated the effects of protein phosphorylation on MSI-1 activity. We showed that MSI-1 function is likely controlled by alterations of its activity rather than its expression levels. Furthermore, we found that MSI-1 is phosphorylated and using mass spectrometry we identified MSI-1 phosphorylation at three residues (T18, S19 and S34). CRISPR-based manipulations of MSI-1 phosphorylation sites revealed that phosphorylation is necessary for MSI-1 function in both short- and long-term aversive olfactory associative memory. Thus, our study provides insight into the mechanisms regulating memory-related MSI-1 activity and may facilitate the development of novel therapeutic approaches.

Abstract Abstract 1282 Emerging evidence is establishing a connection between MDS and spliceosome mutations. Spliceosome including SF3b1, U2AF1 and SRSF2 are frequently and exclusively mutated in myelodysplastic syndromes (MDS) and related myeloid neoplasms. Spliceosome mutations occur at varying frequencies in different disease subtypes. SF3B1 was shown to be highly associated with MDS characterized by increased ring sideroblasts and SRSF2 mutations are more prevalent in chronic myelomonocytic leukemia. In spite of the fact that the recent discovery constitutes a novel class of genomic lesions and defines an entirely new pathogenic pathway of leukaemogenesis, the pathogenesis of spliceosome mutation is not largely understood. To understanding the biological consequences of spliceosomal mutations, we previously reported mutant U2AF1 cause altered RNA splicing, and overexpressed mutant U2AF1 decrease in cell proliferarion. However, currently, no functional analysis of SRSF2 mutation has been published. SRSF2 belongs to the serine/arginine-rich (SR) protein family. SR proteins are a family of RNA binding proteins characterized by one or two RNA recognition motifs (RRMs) and a signature RS domain enriched with arginine and serine repeats (RS domain).Growing body of evidence suggests that SR protein may be directly involved in the process of carcinogenesis. Gene knockout experiment indicated SRSF2 is involved with specific pathways in regulating cell proliferation and genomic stability during mammalian organogenesis. In neck and head tumor, SRSF2 is frequently overexpressed. And upregulated SRSF2 increases missplicing and downregulates E-cadherin expression, which is an important tumor suppressor gene. Therefore SRSF2 potential function in tumorigenesis is suggested in epithelial cancers. SRSF2 mutations with MDS exclusively occur at P95 within an intervening sequence between RRM and RS domains, indicating a gain-of-function nature of these mutations. So, to clarify the biological role of SRSF2 mutations in leukemogenesis, we evaluated the oncogenic role of SRSF mutations by expressing a mutant SRSF2 allele in Jurkat cells. The cells transduced with a tumor-derived SRSF2 allele showed reduced cell proliferation and increased apoptosis compared to the mock and wild type SRSF2-transduced cells. Next we performed in vitro colony assay using a highly purified hematopoietic stem cell population (CD34-c-Kit+ScaI+ Lin-(CD34-KSL) cells) collected from C57BL/6 (B6)-Ly5.1 mouse that was retrovirally transduced with mock, mutant or wild-type SRSF2 construct. The mutant SRSF2-transduced cells showed reduced cell proliferation compared with mock- or wild-type SRSF2 transduced cells. Subsequently, we conducted bone marrow transplantaion assay. We collected CD34-KSL cells from B6-Ly5.1 mouse, and retrovirally transduce mock, mutant or wild-type SRSF2 construct, each harbouring the EGFP marker gene. And these cells were sorted by EGFP marker, and transplanted with competitor cells (B6-Ly5.1/5.2 F1 mice origin) into lethally irradiated B6-Ly5.2 mice. The wild-type SRSF2-transduced cells showed a lower reconstitution capacity than the mock-transduced cells. On the other hand, the recipients of the cells transduced with the mutant SRSF2 showed lower EGFP-positive cell chimaerism than those of the mock- or the wild-type SRSF2-transduced. Therefore, the mutant SRSF2 was indicated to have a negative effect on cellular proliferation capacity in vitro and in vivo, and a gain-of-function nature of these mutations is suggested. These results are similar to the effect of U2AF1 mutant, which we reported mutant U2AF1 transduced TF-1 and HeLa cells present with a decrease in cell proliferation and hematopoietic stem cells expressing mutant U2AF1 also displayed lower reconstitution capacity by competitive reconstitution assay in mice. So far, the mechanism responsible for the growth advantage of mutant cells in patient is unclear. We furthermore observe hematopoietic phenotype of the bone marrow transplanted model mouse. SRSF2 mutations can coexist with mutations in TET2, ASXL1 and RUNX1. Therefore we performed additionally bone marrow transplantation assay, utilizing hematopoietic cells derived from TET2 knockdown mice, as a model of multistep carcinogenesis. We will present the results of our biological assay on the SRSF2 mutations and discuss the pathogenesis of MDS. Disclosures: No relevant conflicts of interest to declare.

Abstract The roles of Heterogeneous nuclear ribonucleoproteins(hnRNPs) in regulating tumor development and progression, either as oncogenes or as tumor suppressors, were well documented. HnRNP C is one of the members of hnRNPs,and differential expression of hnRNP C has been found in series of tumor cells. However, the role of hnRNP C in leukemia has not been reported to date. Here, we report the first novel gene fusion event between HNRNPC and retinoic acid receptor gamma (RARG) in acute myeloid leukemia mimicking acute promyelocytic leukemia. This translocation produced the HNRNPC-RARG fusion gene and its reciprocal, RARG-HNRNPC. A 43-year-old man was referred to our hospital with fever and a sore throat.Laboratory investigations revealed the following patient characteristics: (1) white blood cell count 12 × 109/L (blasts 1% and abnormal promyelocytes 86%). (2) Morphologic analysis of the bone marrow aspirate showed 86.5% microgranular atypical promyelocytes (Figure 1a, 1b). (3) Analysis from flow cytometry showed that the blasts were positive for CD33, CD13, CD45, and cMPO and negative for CD14, CD34, CD16, CD56, HLA-DR, B- or T-cell markers. Thus, the patient started all-trans retinoic acid (ATRA) treatment immediately. Afterwards, chromosomal analysis revealed 47 metaphases, and most of them were involved in t(14;17). Fluorescence in situ hybridization and RT-PCR assays did not identify the PML/RARA, NPM-RARA, PLZF-RARArearrangement. ATRA therapy lasted for 3 weeks, but no response was observed. Next, the patient received 2 cycles of induction chemotherapy until a complete response. Afterwards, he received 6 cycles of chemotherapy. Unfortunately, the leukemia relapsed 1 year later, and all treatments (including ATRA and arsenious acid) failed to produce any effects. The patient died from sepsis. To identify molecular alterations, transcriptome sequencing analysis was performed. A 213-bp RARG-HNRNPC fusion product was specifically amplified from the patient's cDNA, as predicted (Figure 1c). Sanger sequencing showed that RARG exon 9 was fused in-frame to HNRNPC exon 3(Figure 1d). The RARG 5'-region encoding the ligand-binding domain was fused to the HNRNPC3'-region, where a cluster of phosphorylation sites is located(Figure 1e). We also found a reciprocal chimeric transcript. The amplicon size of HNRNPC-RARG fusion was 186-bp (Figure 2a). Sanger sequencing demonstrated that HNRNPC exon 3 was fused in-frame to RARG exon 5 (Figures 2b). The HNRNPC 5'-region encodes an RNA recognition motif (RRM), and the segment from RARG encodes a DNA binding domain (DBD, Figure 2c). HnRNP C ubiquitously expressed RNA-binding protein (RBP) which are believed to influence pre-mRNA metabolism such as splicing, polyadenylation, stability, transport, andtranslation mediated by internal ribosome entry site. HnRNP C also plays an essential role in cell progression and the regulation of several DNA repair proteins. Retinoic acid receptors (RARs) are transcription factors that belong to the nuclear hormone receptor family.RARA, RARB, and RARG are three RARs subtypes which share highly similar sequences and functions. A study showed RARG seems to act as a major regulator maintaining the balance between HSC self-renewal and differentiation. Acute myeloid leukemias mimicking acute promyelocytic leukemia, or acute promyelocytic-like leukemias (APLL), share the same morphology and immunocytochemistry features with typical acute promyelocytic leukemia (APL) except the RARA rearrangements, and little is known about the molecular mechanisms of APLL. The sequences and function of the RARG and RARA are highly alike, and therefore can logically explain the similarity of biological characteristics between the two entities. Three other fusion genes harboring RARG ( including NUP98-RARG , PML-RARG and CPSF6-RARG) have been found in APLL. Unfortunately they showed resistance to treatment with ATRA or ATRA plus arsenic. Moreover, poor prognosis was observed likewise. All the above confirm that RARG rearrangements are not random but recurrent genetic abnormalities. In conclusion, we present a novel HNRNPC-RARG fusion gene and its reciprocal in APLL, and suggest that at least a portion of APLLs have RARG gene rearrangements. We propose that RARG-rearranged APLL may be a novel candidate subtype of acute myelocytic leukemia, or even of APL. Disclosures No relevant conflicts of interest to declare.

SummaryThe expression of various low Mr GTP-binding proteins at various states of differentiation of a human megakaryoblastic leukemia cell line, MEG-01, was analyzed using thermocycle amplification of mRNA and immunoblotting. MEG-01 cells were found to express mRNAs of rap1A, rap1B, rap2B, ralA, rhoA, rac1, rac2, CDC42Hs, rab1, rab3B, rab6, ram and ran, but not rab4, and the proteins of Rap 1, Rap2, RhoA, Rac1, Rac2, Rab3B, Rab4, Rab6 and Rab8 were expressed. Differentiation of MEG-01 cells induced by 100 nM 12-O-tetradecanoylphorbol-13-acetate revealed the considerable increases in mRNA expression of rap1B, rab3B, rabA, ram and ran whereas the levels of rap2B, rhoA and rac1 decreased. During the differentiation process, significant changes in protein levels of Rap1, RhoA, Rac1, Rac2, Rab3B, Rab4 and Rab6 were observed among three subcellular (cytosol, Triton X-100-soluble membrane and -insoluble cytoskeleton) fractions. The present investigation may be useful for the study of the megakaryocyte differentiation.

Mammalian sperm are known to contain various types of RNA. Recently, translation of RNA to proteins occurring during capacitation was reported to be important for sperm function and fertilization. The objective of this study was to examine the change in the distribution of RNA in boar sperm during culture in a capacitation medium containing caffeine by using fluorescence specifically binding to RNA. The sperm-rich fraction from Berkshire boars (n = 4) was diluted (cells mL–1) with modified Modena solution containing 20% seminal fluid, cooled to 15°C for 4 h, and kept at the same temperature until use. Stored, diluted semen was washed by centrifugation (1500 rpm for 35 min at room temperature) in a Percoll gradient (45/90%). A sperm suspension (concentration 1 × 107 cells mL–1) in modified TCM-199 containing 0.4% BSA and 5 mM caffeine was then prepared and cultured in an atmosphere of 5% CO2 in air at 39°C for 1 or 4 h. Before and after culture, sperm were stained by using SYTO RNA Select Green Fluorescence Cell Stain (Molecular Probes, Eugene, OR) according to the manufacturer’s protocol, and then the mounted specimens were observed and the intensity of fluorescence images was measured under a fluorescence microscope (BIOREVO, Keyence, Osaka, Japan). Viability of sperm was also determined following SYBR-Green–propidium iodide staining under a fluorescence microscope. Statistical analyses were carried out by ANOVA and with a Bonferroni-Dunn post-hoc test (P < 0.05). Although the viability of sperm decreased before (96.7%) and 1 h after the start of culture (79.8%), it did not decline until 4 h after the start of culture (80.9%). Before culture, fluorescence indicating the presence of RNA was observed at the head, especially the postacrosomal region and the midpiece region of the sperm. The intensity of fluorescence changed during culture. The fluorescence intensity of RNA at the sperm head region was higher (P < 0.01) at 1 h of culture (36.11 × 104) than before culture (30.50 × 104) and at 4 h of culture (28.60 × 104). The intensity of RNA at the midpiece region was higher (P < 0.01) at 1 h (11.42 × 104) and was lower (P < 0.01) at 4 h of culture (4.93 × 104) than before culture (8.45 × 104). From these results, we concluded that the distribution and content of RNA changes drastically during culture in a capacitation medium containing caffeine. Additional study of the kinetics of sperm RNA during capacitation is ongoing to further understand the post-transcriptional regulation.

Abstract Abstract 2552 The Musashi (MSI) gene family members, MSI1 and MSI2, represent an evolutionarily conserved family of RNA-binding proteins that regulate mRNA translation through binding in their N-termini. High levels of MSI2 protein are associated with increased cell proliferation, decreased cell maturation, more aggressive hematologic malignancy diseases and worse clinical prognosis. Recently obtained data pointed to MSI2 playing an important role in acute myeloid leukemia (AML) and in deadly blast crisis of chronic myeloid leukemia (CML) (Ito et al. 2010 Nature 5; 466). In this study we screened the level of MSI2 mRNA in 49 patients in different phases of CML and with different response to therapy – 18 patients at diagnosis (DG), 5 in major molecular response (MMR), 4 in complete molecular response (CMR), 2 after bone marrow transplantation (BMT), 10 in hematology relaps (HR), 6 in accelerrated phase (AP), and 4 in blast crisis (BC), and in 6 healthy donors. The level of MSI2 mRNA was quantified by real-time reverse-transcriptase-polymerase chain reaction using in-house designed specific primers and TaqMan probe and normalized to B2M endogenous control. Expression ratios were calculated by ΔΔCt method, and the differences between groups were statistically evaluated using Mann Whitney test. We detected MSI2 expression in all samples. The median expression of mRNA MSI2 in patients at DG was 1,43 (0,33–3,28), in MMR 0,52 (0,20–0,62), in CMR 0,37 (0,30–0,63), after BMT 1,28 (1,02–1,54), in HR 0,41 (0,16–0,58), in AP 3,78 (1,94–13,69), in BC 15,17 (2,61–28,15). MSI2 expression was statistically up-regulated in patients in advanced phases of CML (AP, BC) when compared with patients in CP (P<0.0001). The difference between patients in DG and remaining patients in CP was also statistically significant (P= 0,0006). No correlation of MSI2 expression level in DG patients with their responsiveness to treatment, BCR-ABL transcript level or survival was found. No significant differences were observed among groups of patients in MMR, CMR, HR, and after BMT. In addition, in order to check whether MSI2 expression level can serve as a marker of CML progression we also retrospectively screened kinetics of MSI2 transcript in 5 CML patients monitored on average 27 months (18–48). During this period, 3 patients developed HR, 1 patient AP and 1 BC. In BC patient the MSI2 transcript level increased with progression of CML in accordance with the increase of leucocytes and BCR-ABL transcript level. In 1 patient with a rising AP BCR-ABL levels remained constant compared to sevenfold increase of the MSI2 transcript level. On the other hand in HR patients we detected a constant or even decreasing level of MSI2 transcript regardless of the increase of leucocytes and BCR-ABL. In summary, our results confirm the association of high MSI2 mRNA level with advanced phases of CML and indicate that increase of MSI2 mRNA level may serve as a valuable marker of advanced phases of CML. In particular for CML patients with constantly high level of BCR-ABL mRNA the monitoring of MSI2 level can be important tool for early recognition of CML progression. Potential contributions of MSI2 to leukemic pathogenesis and its regulation in CML progression remain unknown. Grant support: NT/12392-4 IGA MZ-CR. Disclosures: No relevant conflicts of interest to declare.

Hamsters were exposed to sodium arsenite (173 mg As/L) in drinking water for 6 days. Equal amounts of proteins from urinary bladder or liver extracts of control and arsenic-treated hamsters were labeled with Cy3 and Cy5 dyes, respectively. After differential in gel electrophoresis and analysis by the DeCyder software, several protein spots were found to be down-regulated and several were up regulated. Our experiments indicated that in the bladder tissues of hamsters exposed to arsenite, transgelin was down-regulated and GST-pi was up-regulated. The loss of transgelin expression has been reported to be an important early event in tumor progression and a diagnostic marker for cancer development [29-32]. Down-regulation of transgelin expression may be associated with the carcinogenicity of inorganic arsenic in the urinary bladder. In the liver of arsenite-treated hamsters, ornithine aminotransferase was up-regulated, and senescence marker protein 30 and fatty acid binding protein were down-regulated. The volume ratio changes of these proteins in the bladder and liver of hamsters exposed to arsenite were significantly different than that of control hamsters. Introduction Chronic exposure to inorganic arsenic can cause cancer of the skin, lungs, urinary bladder, kidneys, and liver [1-6]. The molecular mechanisms of the carcinogenicity and toxicity of inorganic arsenic are not well understood [7-9). Humans chronically exposed to inorganic arsenic excrete MMA(V), DMA(V) and the more toxic +3 oxidation state arsenic biotransformants MMA(III) and DMA (III) in their urine [10, 11], which are carcinogen [12]· After injection of mice with sodium arsenate, the highest concentrations of the very toxic MMA(III) and DMA(III) were in the kidneys and urinary bladder tissue, respectively, as shown by experiments of Chowdhury et al [13]. Many mechanisms of arsenic toxicity and carcinogenicity have been suggested [1, 7, 14] including chromosome abnormalities [15], oxidative stress [16, 17], altered growth factors [18], cell proliferation [19], altered DNA repair [20], altered DNA methylation patterns [21], inhibition of several key enzymes [22], gene amplification [23] etc. Some of these mechanisms result in alterations in protein expression. Methods for analyzing multiple proteins have advanced greatly in the last several years. In particularly, mass spectrometry (MS) and tandem MS (MS/MS) are used to analyze peptides following protein isolation using two-dimensional (2-D) gel electrophoresis and proteolytic digestion [24]. In the present study, Differential In Gel Electrophoresis (DIGE) coupled with Mass Spectrometry (MS) has been used to study some of the proteomic changes in the urinary bladder and liver of hamsters exposed to sodium arsenite in their drinking water. Our results indicated that transgelin was down-regulated and GST-pi was up-regulated in the bladder tissues. In the liver tissues ornithine aminotransferase was up-regulated, and senescence marker protein 30, and fatty acid binding protein were down-regulated. Materials and Methods Chemicals Tris, Urea, IPG strips, IPG buffer, CHAPS, Dry Strip Cover Fluid, Bind Silane, lodoacetamide, Cy3 and Cy5 were from GE Healthcare (formally known as Amersham Biosciences, Uppsala, Sweden). Thiourea, glycerol, SDS, DTT, and APS were from Sigma-Aldrich (St. Louis, MO, USA). Glycine was from USB (Cleveland, OH, USA). Acrylamide Bis 40% was from Bio-Rad (Hercules, CA, USA). All other chemicals and biochemicals used were of analytical grade. All solutions were made with Milli-Q water. Animals Male hamsters (Golden Syrian), 4 weeks of age, were purchased from Harlan Sprague Dawley, USA. Upon arrival, hamsters were acclimated in the University of Arizona animal care facility for at least 1 week and maintained in an environmentally controlled animal facility operating on a 12-h dark/12-h light cycle and at 22-24°C. They were provided with Teklad (Indianapolis, IN) 4% Mouse/Rat Diet # 7001 and water, ad libitum, throughout the acclimation and experimentation periods. Sample preparation and labelling Hamsters were exposed to sodium arsenite (173 mg) in drinking water for 6 days and the control hamsters were given tap water. On the 6th day hamsters were decapitated rapidly by guillotine. Urinary bladder tissues and liver were removed, blotted on tissue papers (Kimtech Science, Precision Wipes), and weighed. Hamster urinary bladder or liver tissues were homogenized in lysis buffer (30mMTris, 2M thiourea, 7M urea, and 4% w/w CHAPS adjusted to pH 8.5 with dilute HCI), at 4°C using a glass homogenizer and a Teflon coated steel pestle; transferred to a 5 ml acid-washed polypropylene tube, placed on ice and sonicated 3 times for 15 seconds. The sonicate was centrifuged at 12,000 rpm for 10 minutes at 4°C. Small aliquots of the supernatants were stored at -80°C until use (generally within one week). Protein concentration was determined by the method of Bradford [25] using bovine serum albumin as a standard. Fifty micrograms of lysate protein was labeled with 400 pmol of Cy3 Dye (for control homogenate sample) and Cy5 Dye (for arsenic-treated urinary bladder or liver homogenate sample). The samples containing proteins and dyes were incubated for 30 min on ice in the dark. To stop the labeling reaction, 1uL of 10 mM lysine was added followed by incubation for 10 min on ice in the dark. To each of the appropriate dye-labeled protein samples, an additional 200 ug of urinary bladderor liver unlabeled protein from control hamster sample or arsenic-treated hamster sample was added to the appropriate sample. Differentially labeled samples were combined into a single Microfuge tube (total protein 500 ug); protein was mixed with an equal volume of 2x sample buffer [2M thiourea, 7M urea, pH 3-10 pharmalyte for isoelectric focusing 2% (v/v), DTT 2% (w/v), CHAPS 4% (w/v)]; and was incubated on ice in the dark for 10 min. The combined samples containing 500 ug of total protein were mixed with rehydration buffer [CHAPS 4% (w/v), 8M urea, 13mM DTT, IPG buffer (3-10) 1% (v/v) and trace amount of bromophenol blue]. The 450 ul sample containing rehydration buffer was slowly pipetted into the slot of the ImmobilinedryStripReswelling Tray and any large bubbles were removed. The IPG strip (linear pH 3-10, 24 cm) was placed (gel side down) into the slot, covered with drystrip cover fluid (Fig. 1), and the lid of the Reswelling Tray was closed. The ImmobillineDryStrip was allowed to rehydrate at room temperature for 24 hours. First dimension Isoelectric focusing (IEF) The labeled sample was loaded using the cup loading method on universal strip holder. IEF was then carried out on EttanIPGphor II using multistep protocol (6 hr @ 500 V, 6 hr @ 1000 V, 8 hr @ 8000 V). The focused IPG strip was equilibrated in two steps (reduction and alkylation) by equilibrating the strip for 10 min first in 10 ml of 50mM Tris (pH 8.8), 6M urea, 30% (v/v) glycerol, 2% (w/v) SDS, and 0.5% (w/v) DTT, followed by another 10 min in 10 ml of 50mM Tris (pH 8.8), 6M urea, 30% (v/v) glycerol, 2% (w/v) SDS, and 4.5% (w/v) iodoacetamide to prepare it for the second dimension electrophoresis. Second dimension SDS-PAGE The equilibrated IPG strip was used for protein separation by 2D-gel electrophoresis (DIGE). The strip was sealed at the top of the acrylamide gel for the second dimension (vertical) (12.5% polyacrylamide gel, 20x25 cm x 1.5 mm) with 0.5% (w/v) agarose in SDS running buffer [25 mMTris, 192 mM Glycine, and 0.1% (w/v) SDS]. Electrophoresis was performed in an Ettan DALT six electrophoresis unit (Amersham Biosciences) at 1.5 watts per gel, until the tracking dye reached the anodic end of the gel. Image analysis and post-staining The gel then was imaged directly between glass plates on the Typhoon 9410 variable mode imager (Sunnyvale, CA, USA) using optimal excitation/emission wavelength for each DIGE fluor: Cy3 (532/580 nm) and Cy5 (633/670 nm). The DIGE images were previewed and checked with Image Quant software (GE Healthcare) where all the two separate gel images could be viewed as a single gel image. DeCyde v.5.02 was used to analyze the DIGE images as described in the Ettan DIGE User Manual (GE Healthcare). The appropriate up-/down regulated spots were filtered based on an average volume ratio of ± over 1.2 fold. After image acquisition, the gel was fixed overnight in a solution containing 40% ethanol and 10% acetic acid. The fixed gel was stained with SyproRuby (BioRad) according to the manufacturer protocol (Bio-Rad Labs., 2000 Alfred Nobel Drive, Hercules, CA 94547). Identification of proteins by MS Protein spot picking and digestion Sypro Ruby stained gels were imaged using an Investigator ProPic and HT Analyzer software, both from Genomic Solutions (Ann Arbor, MI). Protein spots of interest that matched those imaged using the DIGE Cy3/Cy5 labels were picked robotically, digested using trypsin as described previously [24] and saved for mass spectrometry identification. Liquid chromatography (LC)- MS/MS analysis LC-MS/MS analyses were carried out using a 3D quadrupole ion trap massspectrometer (ThermoFinnigan LCQ DECA XP PLUS; ThermoFinnigan, San Jose, CA) equipped with a Michrom Paradigm MS4 HPLC (MichromBiosources, Auburn, CA) and a nanospray source, or with a linear quadrupole ion trap mass spectrometer (ThermoFinnigan LTQ), also equipped with a Michrom MS4 HPLC and a nanospray source. Peptides were eluted from a 15 cm pulled tip capillary column (100 um I.D. x 360 um O.D.; 3-5 um tip opening) packed with 7 cm Vydac C18 (Vydac, Hesperia, CA) material (5 µm, 300 Å pore size), using a gradient of 0-65% solvent B (98% methanol/2% water/0.5% formic acid/0.01% triflouroacetic acid) over a 60 min period at a flow rate of 350 nL/min. The ESI positive mode spray voltage was set at 1.6 kV, and the capillary temperature was set at 200°C. Dependent data scanning was performed by the Xcalibur v 1.3 software on the LCQ DECA XP+ or v 1.4 on the LTQ [27], with a default charge of 2, an isolation width of 1.5 amu, an activation amplitude of 35%, activation time of 50 msec, and a minimal signal of 10,000 ion counts (100 ion counts on the LTQ). Global dependent data settings were as follows: reject mass width of 1.5 amu, dynamic exclusion enabled, exclusion mass width of 1.5 amu, repeat count of 1, repeat duration of a min, and exclusion duration of 5 min. Scan event series were included one full scan with mass range of 350-2000 Da, followed by 3 dependent MS/MS scans of the most intense ion. Database searching Tandem MS spectra of peptides were analyzed with Turbo SEQUEST, version 3.1 (ThermoFinnigan), a program that allows the correlation of experimental tandem MS data with theoretical spectra generated from known protein sequences. All spectra were searched against the latest version of the non redundant protein database from the National Center for Biotechnology Information (NCBI 2006; at that time, the database contained 3,783,042 entries). Statistical analysis The means and standard error were calculated. The Student's t-test was used to analyze the significance of the difference between the control and arsenite exposed hamsters. P values less than 0.05 were considered significant. The reproducibility was confirmed in separate experiments. Results Analysis of proteins expression After DIGE (Fig. 1), the gel was scanned by a Typhoon Scanner and the relative amount of protein from sample 1 (treated hamster) as compared to sample 2 (control hamster) was determined (Figs. 2, 3). A green spot indicates that the amount of protein from sodium arsenite-treated hamster sample was less than that of the control sample. A red spot indicates that the amount of protein from the sodium arsenite-treated hamster sample was greater than that of the control sample. A yellow spot indicates sodium arsenite-treated hamster and control hamster each had the same amount of that protein. Several protein spots were up-regulated (red) or down-regulated (green) in the urinary bladder samples of hamsters exposed to sodium arsenite (173 mg As/L) for 6 days as compared with the urinary bladder of controls (Fig. 2). In the case of liver, several protein spots were also over-expressed (red) or under-expressed (green) for hamsters exposed to sodium arsenite (173 mg As/L) in drinking water for 6 days (Fig. 3). The urinary bladder samples were collected from the first and second experiments in which hamsters were exposed to sodium arsenite (173 mg As/L) in drinking water for 6 days and the controls were given tap water. The urinary bladder samples from the 1st and 2nd experiments were run 5 times in DIGE gels on different days. The protein expression is shown in Figure 2 and Table 1. The liver samples from the 1st and 2nd experiments were also run 3 times in DIGE gels on different days. The proteins expression were shown in Figure 3 and Table 2. The volume ratio changed of the protein spots in the urinary bladder and liver of hamsters exposed to arsenite were significantly differences than that of the control hamsters (Table 1 and 2). Protein spots identified by LC-MS/MS Bladder The spots of interest were removed from the gel, digested, and their identities were determined by LC-MS/MS (Fig. 2 and Table 1). The spots 1, 2, & 3 from the gel were analyzed and were repeated for the confirmation of the results (experiments; 173 mg As/L). The proteins for the spots 1, 2, and 3 were identified as transgelin, transgelin, and glutathione S-transferase Pi, respectively (Fig. 2). Liver We also identified some of the proteins in the liver samples of hamsters exposed to sodium arsenite (173 mg As/L) in drinking water for 6 days (Fig. 3). The spots 4, 5, & 6 from the gels were analyzed and were repeated for the confirmation of the results. The proteins for the spots 4, 5, and 6 were identified as ornithine aminotransferase, senescence marker protein 30, and fatty acid binding protein, respectively (Fig. 3) Discussion The identification and functional assignment of proteins is helpful for understanding the molecular events involved in disease. Weexposed hamsters to sodium arsenite in drinking water. Controls were given tap water. DIGE coupled with LC-MS/MS was then used to study the proteomic change in arsenite-exposed hamsters. After electrophoresis DeCyder software indicated that several protein spots were down-regulated (green) and several were up-regulated (red). Our overall results as to changes and functions of the proteins we have studied are summarized in Table 3. Bladder In the case of the urinary bladder tissue of hamsters exposed to sodium arsenite (173 mg As/L) in drinking water for 6 days, transgelin was down-regulated and GST-pi was up-regulated. This is the first evidence that transgelin is down-regulated in the bladders of animals exposed to sodium arsenite. Transgelin, which is identical to SM22 or WS3-10, is an actin cross linking/gelling protein found in fibroblasts and smooth muscle [28, 29]. It has been suggested that the loss of transgelin expression may be an important early event in tumor progression and a diagnostic marker for cancer development [30-33]. It may function as a tumor suppressor via inhibition of ARA54 (co-regulator of androgen receptor)-enhanced AR (androgen receptor) function. Loss of transgelin and its suppressor function in prostate cancer might contribute to the progression of prostate cancer [30]. Down-regulation of transgelin occurs in the urinary bladders of rats having bladder outlet obstruction [32]. Ras-dependent and Ras-independent mechanisms can cause the down regulation of transgelin in human breast and colon carcinoma cell lines and patient-derived tumorsamples [33]. Transgelin plays a role in contractility, possibly by affecting the actin content of filaments [34]. In our experiments loss of transgelin expression may be associated or preliminary to bladder cancer due to arsenic exposure. Arsenite is a carcinogen [1]. In our experiments, LC-MS/MS analysis showed that two spots (1 and 2) represent transgelin (Fig. 2 and Table 1). In human colonic neoplasms there is a loss of transgelin expression and the appearance of transgelin isoforms (31). GST-pi protein was up-regulated in the bladders of the hamsters exposed to sodium arsenite. GSTs are a large family of multifunctional enzymes involved in the phase II detoxification of foreign compounds [35]. The most abundant GSTS are the classes alpha, mu, and pi classes [36]. They participate in protection against oxidative stress [37]. GST-omega has arsenic reductase activity [38]. Over-expression of GST-pi has been found in colon cancer tissues [39]. Strong expression of GST-pi also has been found in gastric cancer [40], malignant melanoma [41], lung cancer [42], breast cancer [43] and a range of other human tumors [44]. GST-pi has been up-regulated in transitional cell carcinoma of human urinary bladder [45]. Up-regulation of glutathione – related genes and enzyme activities has been found in cultured human cells by sub lethal concentration of inorganic arsenic [46]. There is evidence that arsenic induces DNA damage via the production of ROS (reactive oxygen species) [47]. GST-pi may be over-expressed in the urinary bladder to protect cells against arsenic-induced oxidative stress. Liver In the livers of hamsters exposed to sodium arsenite, ornithine amino transferase was over-expressed, senescence marker protein 30 was under-expressed, and fatty acid binding protein was under-expressed. Ornithine amino transferase has been found in the mitochondria of many different mammalian tissues, especially liver, kidney, and small intestine [48]. Ornithine amino transferase knockdown inhuman cervical carcinoma and osteosarcoma cells by RNA interference blocks cell division and causes cell death [49]. It has been suggested that ornithine amino transferase has a role in regulating mitotic cell division and it is required for proper spindle assembly in human cancer cells [49]. Senescence marker protein-30 (SMP30) is a unique enzyme that hydrolyzes diisopropylphosphorofluoridate. SMP30, which is expressed mostly in the liver, protects cells against various injuries by stimulating membrane calcium-pump activity [50]. SMP30 acts to protect cells from apoptosis [51]. In addition it protects the liver from toxic agents [52]. The livers of SMP30 knockout mice accumulate phosphatidylethanolamine, cardiolipin, phosphatidyl-choline, phosphatidylserine, and sphingomyelin [53]. Liver fatty acid binding protein (L-FABP) also was down- regulated. Decreased liver fatty acid-binding capacity and altered liver lipid distribution hasbeen reported in mice lacking the L-FABP gene [54]. High levels of saturated, branched-chain fatty acids are deleterious to cells and animals, resulting in lipid accumulation and cytotoxicity. The expression of fatty acid binding proteins (including L-FABP) protected cells against branched-chain saturated fatty acid toxicity [55]. Limitations: we preferred to study the pronounced spots seen in DIGE gels. Other spots were visible but not as pronounced. Because of limited funds, we did not identify these others protein spots. In conclusion, urinary bladders of hamsters exposed to sodium arsenite had a decrease in the expression of transgelin and an increase in the expression of GST-pi protein. Under-expression of transgelin has been found in various cancer systems and may be associated with arsenic carcinogenicity [30-33). Inorganic arsenic exposure has resulted in bladder cancer as has been reported in the past [1]. Over-expression of GST-pi may protect cells against oxidative stress caused by arsenite. In the liver OAT was up regulated and SMP-30 and FABP were down regulated. These proteomic results may be of help to investigators studying arsenic carcinogenicity. The Superfund Basic Research Program NIEHS Grant Number ES 04940 from the National Institute of Environmental Health Sciences supported this work. Additional support for the mass spectrometry analyses was provided by grants from NIWHS ES06694, NCI CA023074 and the BIOS Institute of the University of Arizona. Acknowledgement The Author wants to dedicate this paper to the memory of his former supervisor Dr. H. VaskenAposhian who passed away in September 6, 2019. He was an emeritus professor of the Department of Molecular and Cellular Biology at the University of Arizona. This research work was done under his sole supervision and with his great contribution.I also would like to thanks Dr. George Tsapraills, Center of Toxicology, The University of Arizona for identification of proteins by MS. References NRC (National Research Council), Arsenic in Drinking Water, Update to the 1999 Arsenic in Drinking Water Report. National Academy Press, Washington, DC 2001. Hopenhayn-Rich, C.; Biggs, M. L.; Fuchs, A.; Bergoglio, R.; et al. Bladder cancer mortality with arsenic in drinking water in Argentina. Epidemiology 1996, 7, 117-124. Chen, C.J.; Chen, C. W.; Wu, M. M.; Kuo, T. L. Cancer potential in liver, lung, bladder, and kidney due to ingested inorganic arsenic in drinking water. J. Cancer. 1992, 66, 888-892. IARC (International Agency for Research on Cancer), In IARC monograph on the evaluation of carcinogenicity risk to humans? Overall evaluation of carcinogenicity: an update of IARC monographs 1-42 (suppl. 7), International Agency for Research on Cancer, Lyon, France, 1987, pp. 100-106. Rossman, T. G.; Uddin, A. N.; Burns, F. J. Evidence that arsenite acts as a cocarcinogen in skin cancer. Appl. Pharmacol. 2004, 198, 394 404. Smith, A. H.; Hopenhayn-Rich, C.; Bates, M. N.; Goeden, H. M.; et al. Cancer risks from arsenic in drinking water. Health Perspect. 1992, 97, 259-267. Aposhian, H. V.; Aposhian, M. M. Arsenic toxicology: five questions. Res. Toxicol. 2006, 19, 1-15. Goering, P. L.; Aposhian, H. V.; Mass, M. J.; Cebrián, M., et al. The enigma of arsenic carcinogenesis: role of metabolism. Sci. 1999, 49, 5-14. Waalkes, M. P.; Liu, J.; Ward, J. M.; Diwan, B. A. Mechanisms underlying arsenic carcinogenesis: hypersensitivity of mice exposed to inorganic arsenic during gestation. 2004, 198, 31-38. Aposhian, H. V.; Gurzau, E. S.; Le, X. C.; Gurzau, A.; et al. Occurrence of monomethylarsonous acid in urine of humans exposed to inorganic arsenic. Res. Toxicol. 2000, 13, 693-697. Del Razo, L. M.; Styblo, M.; Cullen, W. R.; Thomas, D. J. Determination of trivalent methylated arsenicals in biological matrices. Appl. Pharmacol. 2001, 174, 282-293. Styblo, M.; Drobna, Z.; Jaspers, I.; Lin, S.; Thomas, D. J.; The role of biomethylation in toxicity and carcinogenicity of arsenic: a research update. Environ. Health Perspect. 2002, 5, 767-771. Chowdhury, U. K.; Zakharyan, R. A.; Hernandez, A.; Avram, M. D.; et al. Glutathione-S-transferase-omega [MMA(V) reductase] knockout mice: Enzyme and arsenic species concentrations in tissues after arsenate administration. Appl. Pharmaol. 2006, 216, 446-457. Kitchin, K. T. Recent advances in arsenic carcinogenesis: modes of action, animal model systems, and methylated arsenic metabolites. Appl. Pharmacol. 2001, 172, 249-261. Beckman, G.; Beckman, L.; Nordenson, I. Chromosome aberrations in workers exposed to arsenic. Health Perspect. 1977, 19, 145-146. Yamanaka, K.; Hoshino, M.; Okanoto, M.; Sawamura, R.; et al. Induction of DNA damage by dimethylarsine, a metabolite of inorganic arsenics, is for the major part likely due to its peroxyl radical. Biophys. Res. Commun. 1990, 168, 58-64. Yamanaka, K.; Okada, S. Induction of lung-specific DNA damage by metabolically methylated arsenics via the production of free radicals. Health Perspect. 1994, 102, 37-40. Simeonova, P. P.; Luster, M. I. Mechanisms of arsenic carcinogenicity:Genetic or epigenetic mechanisms? Environ. Pathol. Toxicol. Oncol. 2000, 19, 281-286. Popovicova, J.; Moser, G. J.; Goldsworthy, T. L.; Tice, R. R, Carcinogenicity and co-carcinogenicity of sodium arsenite in p53+/- male mice. 2000, 54, 134. Li, J. H.; Rossman, T. G. Mechanism of co-mutagenesis of sodium arsenite with N-methyl-N-nitrosourea. Trace Elem. 1989, 21, 373-381. Zhao, C. Q.; Young, M. R.; Diwan, B. A.; Coogan, T. P.; et al. Association of arsenic-induced malignant transformation with DNA hypomethylation and aberrant gene expression. Proc. Natl. Acad. Sci. USA, 1997, 94, 10907-10912. Abernathy, C. O.; Lui, Y. P.; Longfellow, D.; Aposhian, H. V.; et al. Arsenic: Health effects, mechanisms of actions and research issues. Health Perspect. 1999, 107, 593-597. Lee, T. C.; Tanaka, N.; Lamb, P. W.; Gilmer, T. M.; et al. Induction of gene amplification by arsenic. 1988, 241, 79-81. Lantz, R. C.; Lynch, B. J.; Boitano, S.; Poplin, G. S.; et al. Pulmonary biomarkers based on alterations in protein expression after exposure to arsenic. Health Perspect. 2007, 115, 586-591. Bradford, M.M. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Biochem. 1976, 72, 248-254. Chowdhury, U. K.; Aposhian, H. V. Protein expression in the livers and urinary bladders of hamsters exposed to sodium arsenite. N. Y. Acad. Sci. 2008, 1140, 325-334. Andon, N. L.; Hollingworth, S.; Koller, A.; Greenland, A. J.; et al. Proteomic characterization of wheat amyloplasts using identification of proteins by Tandem Mass Spectrometry. 2002, 2, 1156-1168. Shapland, C.; Hsuan, J. J.; Totty, N. F.; Lawson, D. Purification and properties of transgelin: a transformation and shape change sensitive actin-gelling protein. Cell Biol. 1993, 121, 1065-1073. Lawson, D.; Harrison, M.; Shapland, C. Fibroblast transgelin and smooth muscle SM22 alpha are the same protein, the expression of which is down-regulated in may cell lines. Cell Motil. Cytoskeleton. 1997, 38, 250-257. Yang, Z.; Chang, Y- J.; Miyamoto, H.; Ni, J.; et al. Transgelin functions as a suppressor via inhibition of ARA54-enhanced androgen receptor transactivation and prostate cancer cell grown. Endocrinol. 2007, 21, 343-358. Yeo, M.; Kim, D- K.; Park, H. J.; Oh, T. Y.; et al. Loss of transgelin in repeated bouts of ulcerative colitis-induced colon carcinogenesis. 2006, 6, 1158-1165. Kim, H- J.; Sohng, I.; Kim, D- H.; Lee, D- C.; et al. Investigation of early protein changes in the urinary bladder following partial bladder outlet obstruction by proteomic approach. Korean Med. Sci. 2005, 20, 1000-1005. Shields, J. M.; Rogers-Graham, K.; Der, C. J. Loss of transgelin in breast and colon tumors and in RIE-1 cells by Ras deregulation of gene expression through Raf-independent pathways. Biol. Chem. 2002, 277, 9790-9799. Zeiden, A.; Sward, K.; Nordstrom, J.; Ekblad, E.; et al. Ablation of SM220c decreases contractility and actin contents of mouse vascular smooth muscle. FEBS Lett. 2004, 562, 141-146. Hoivik, D.; Wilson, C.; Wang, W.; Willett, K.; et al. Studies on the relationship between estrogen receptor content, glutathione S-transferase pi expression, and induction by 2, 3, 7, 8-tetrachlorodibenzo-p-dioxin and drug resistance in human breast cancer cells. Biochem. Biophys. 1997, 348, 174-182. Hayes, J. D.; Pulford. D. J. The glutathione S-transferase super gene family: regulation of GST and the contribution of the isoenzymes to cancer chemoprotection and drug resistance. Critical Rev. Biochem. Mol. Biol. 1995, 30, 445-600. Zhao, T.; Singhal, S. S.; Piper, J. T.; Cheng, J.; et al. The role of human glutathione S-transferases hGSTA1-1 and hGSTA2-2 in protection against oxidative stress. Biochem. Biophys. 1999, 367, 216-224. Zakharyan, R. A.; Sampayo-Reyes, A.; Healy, S. M.; Tsaprailis, G.; et al. Human monomethylarsonic acid (MMA) reductase is a member of the glutathione-S-transferase superfamily. Res. Toxicol. 2001, 14, 1051-1057. Tsuchida, S.; Sekine, Y.; Shineha, R.; Nishihira, T.; et al. Elevation of the placental glutathione S-transferase form (GST-PI) in tumor tissues and the levels in sera of patients with cancer. Cancer Res. 1989, 43, 5225-5229. Tsutsumi, M.; Sugisaki, T.; Makino, T.; Miyagi, N.; et al. Oncofetal expression of glutathione S-transferase placental form in human stomach carcinomas. Gann. 1987, 78, 631-633. Mannervik, B.; Castro, V. M.; Danielson, U. H.; Tahir, M. K.; et al. Expression of class Pi glutathione transferase in human malignant melanoma cells. Carcinogenesis (Lond.). 1987, 8, 1929-1932. Di llio, C.; Del Boccio, G.; Aceto, A.; Casaccia, R.; et al. Elevation of glutathione transferase activity in human lung tumor. Carcinogenesis (Lond.). 1988, 9, 335-340. Sreenath, A. S.; Ravi, K. K.; Reddy, G. V.; Sreedevi, B.; et al. Evidence for the association of synaptotagmin with glutathione S- transferase: implications for a novel function in human breast cancer. Clinical Biochem. 2005, 38, 436-443. Shea, T. C.; Kelley S. L.; Henner, W. D. Identification of an anionic form ofglutathione transferase present in many human tumors and human tumor cell lines. Cancer Res. 1988, 48, 527-533. Simic, T.; Mimic-Oka, J.; Savic-Radojevic, A.; Opacic, M.; et al. Glutathione S- transferase T1-1 activity upregulated in transitional cell carcinoma of urinary bladder. 2005, 65, 1035-1040. Schuliga, M.; Chouchane, S.; Snow, E. T. Up-regulation of glutathione - related genes and enzyme activities in cultured human cells by sub-lethal concentration of inorganic arsenic. Sci. 2002, 70, 183-192. Matsui, M.; Nishigori, C.; Toyokuni, S.; Takada, J.; et al. The role of oxidative DNA damage in human arsenic carcinogenesis: detection of 8 hydroxy-2'-deoxyguanosine in arsenic-related Bowen's disease. Invest. Dermatol. 1999, 113, 26-31. Sanada, Y.; Suemori, I.; Katunuma, N. Properties of ornithine aminotransferase from rat liver, kidney, and small intestine. Biophys. Acta. 1970, 220, 42-50. Wang, G.; Shang, L.; Burgett, A. W. G.; Harran, P. G.; et al. Diazonamide toxins reveal an unexpected function for ornithine d-amino transferase in mitotic cell division. PNAS, 2007, 104, 2068-2073. Fujita, T.; Inoue, H.; Kitamura, T.; Sato, N.; et al. Senescence marker protein-30 (SMP30) rescues cell death by enhancing plasma membrane Caat-pumping activity in hep G2 cells. Biophys. Res. Commun. 1998, 250, 374-380. Ishigami, A.; Fujita, T.; Handa, S.; Shirasawa, T.; et al. Senescence marker protein-30 knockout mouse liver is highly susceptible to tumors necrosis factor-∞ and fas-mediated apoptosis. J. Pathol. 2002, 161, 1273-1281. Kondo, Y.; Ishigami, A.; Kubo, S.; Handa, S.; et al. Senescence marker protein-30is a unique enzyme that hydrolyzes diisopropylphosphorofluoridate in the liver. FEBS Letters. 2004, 570, 57-62. Ishigami, A.; Kondo, Y.; Nanba, R.; Ohsawa, T.; et al. SMP30 deficiency in mice causes an accumulation of neutral lipids and phospholipids in the liver and shortens the life span. Biophys. Res. Commun. 2004, 315, 575-580. Martin, G. G.; Danneberg, H.; Kumar, L. S.; Atshaves, B. P.; et al. Decreased liver fatty acid binding capacity and altered liver lipid distribution in mice lacking the liver fatty acid binding protein gene. Biol. Chem. 2003, 278, 21429-21438. Atshaves, B. P.; Storey, S. M.; Petrescu, A.; Greenberg, C. C.; et al. Expression of fatty acid binding proteins inhibits lipid accumulation and alters toxicity in L cell fibroblasts. J. Physiol. Cell Physiol. 2002, 283, C688-2703.

Introduction: There are numerous methods of isolating and detecting organisms that are similar and closely related; one of the most reliable method is molecular typing of 16S rRNA. Apart from being omnipresent as a multigene family, or operons; it is evolutionarily stable; the 16S rRNA gene (1,500 bp) is large enough for informatics purposes. Materials and Method: This study employed molecular sequencing of 16S rRNA by Sanger method to reveal the specific organisms’ nucleotides and blasting (BLASTn) to show the similarities between the resulting organisms and existing organisms. The 16S rRNA remains the best choice of identification process for bacteria because of its distinguishing sizes and evolutionary stability. Results: All isolates were Gram positive rods and were positive in Biochemical tests such as oxidase, catalase, citrate, and protease but were in turn negative in coagulase and indole test tests. On sensitivity test; 80% of all the isolates were resistant to common antibiotics except ciprofloxacin and ceftriaxone. Based on the sequence difference in the variable region (V1) of 16S rRNA as observed from the molecular sequencing results; four isolates out of ten were identified. Six were different strains of B cereus. Others isolates include: wiedmannii, thuringensis, toyonensis and pseudomycoides. Sequence analysis of the primer annealing sites showed that there is no clear‐cut difference in the conserved region of 16S rRNA, and in the gyrB gene, between B. cereus and B. thuringiensis strains. Phylogenetic analysis showed that four isolates showed high similarity to each other; hence the limited number of deletions when subjected to alignments by maximum neighborhood joining parsimony using MEGA X software. B. toyonensis, B. wiedmannii and thuringensis were distantly related. Introduction Authors Pathogens cause illness and death in some countries and it also causes infections and gastrointestinal diseases in other countries thereby causing public health concern. Pathogens are organisms capable of causing diseases. Reliable methods are needed for the detection of pathogens due to pathogen evolution as a result of new human habits or new industrial practices. Microbial classification of organisms ranges from genus to specie level depending upon the technique used either phenotypic or genotypic. Presently, molecular methods now obtain advances to allow utilization in microbiology [1]. There are numerous molecular methods which are of fast and simple application to the detection of pathogen. Among the pathogens involved in human health, Bacillus cereus is interesting due to their ability to survive in various habitats [2]. The genus Bacillus is aerobic or facultative anaerobic bacteria, gram positive spore forming rod shaped bacteria. Which can be characterized by two morphological forms, the vegetative cell which range from 1.02 to 1.2 um in width and from 3.0 to 5.0 in length, it can be straight or slightly curve, motile or non-motile, and the endospore (the non-swelling sporangium). The genus Bacillus is been characterized by the presence of endospore, which is not more than one per cell and they are resistant to many adverse environmental conditions such as heat, radiation, cold and disinfectants. It can also respire either in the presence or absence of oxygen [3]. Cell diameter of Bacillus cereus, sporangium and catalase test do not allow differentiation, where as important in differentiation among B. anthracis, B. cereus, B. thuringiensis can be considered by parasporal crystals and the presence of capsule. [4] Showed a B. thuringiensis strain capable of producing a capsule resembling that of B. anthracis. Most species of the genus display a great kind in physiological characteristics such as degradation of cellulose, starch, pectin, agar, hydrocarbons, production of enzymes and antibiotics and other characteristic such as acidophile, alkalinophile, psychrophile, and thermophile's which allows them to adapt to various environmental conditions [5]. In differentiating between species of the genus Bacillus it was difficult at early attempts when endospore formation and aerobic respiration were the main character used for classification. As reported by many authors that at molecular method level, the differentiation between B. thuringiensis and B. cereus is also very difficult. cereus can survive at the temperature between 4°c and 55°c. The mesophile strains can grow between the temperature of 10°c and 42°c, while psychotropic strains can survive at 4°c, whereas other strains are able to grow at 52 to 55°c. B. cereus vegetative cells grow at pH between 1.0 and 5.2. Heat resistant strain can survive and multiply in wet low acid foods in temperature ranging from 5 to 52°c. The survivability of B. cereus spores at 95°c decreases when the pH level decreases from 6.2 to 4.7 [6]. B. cereus can grow in the presence of salt with concentration up to 7.5% depending on the pH value. thuringiensis possesses a protein crystal that is toxic to insects. This toxin protein was first known as parasporal crystalline inclusion but was later referred to as π - endotoxin or in other ways known as insecticidal crystal protein [7]. Strains of B. thuringiensis bacteria possess a wide range of specificity in various orders of insects such as Lepidoptera, dipteral, coleoptera. These strains of bacteria produce crystalline proteins known as cry protein during sporulation. When B. thuringiensis infects an insects, it will cause the insect to loose appetite, enhances slow movement and over time the insect will die due to crystals of proteins that have been dissolved in the insect's stomach. In the cultivation of vegetable crops, the plant can be attack by many types of pests. Hence, in overcoming pest attacks farmers often use pesticides that contain active synthetic materials. Many negative effects arise from the folly use of chemical pesticides. Among the negative effect is the increase of pest population, resistance, death of natural enemy population and increase in residue level on Agricultural product which makes it unsafe for public consumption [8]. Therefore, it is necessary to find an alternative method in the control of crop pest. The best alternative that can be done is to replace the chemical insecticide with biological control which involves the use of living things in the form of microorganisms. In these profiling microbial communities, the main objective is to identify which bacteria and how much they are present in the environments. Most microbial profiling methods focus on the identification and quantification of bacteria with already sequenced genomes. Further, most methods utilize information obtained from entire genomes. Homology-based methods such as [1–4] classify sequences by detecting homology in reads belonging to either an entire genome or only a small set of marker genes. Composition-based methods generally use conserved compositional features of genomes for classification and as such they utilize less computational resources.Using the 16S rRNA gene instead of whole genome information is not only computational efficient but also economical; Illumina indicated that targeted sequencing of a focused region of interest reduces sequencing costs and enables deep sequencing, compared to whole-genome sequencing. On the other hand, as observed by [8], by focusing exclusively on one gene, one might lose essential information for advanced analyses. We, however, will provide an analysis that demonstrates that at least in the context of oral microbial communities, the 16S rRNA gene retains sufficient information to allow us detect unknown bacteria [9, 10]. This study aimed at employing 16S rRNA as an instrument of identification of seemingly close Bacillus species. Abbreviations BLAST, Basic Local Alignment sequence Tools; PCR, Polymerase Chains reactions; rRNA, ribosomal RNA; Material and methods T Sample collection. Soil samples were collected from three sources from Rice, Sugar Cane, vegetables and abandoned farmland in January 2019. The samples were labeled serially from Sample 1 to Sample 10 (S1 to S10). Bacterial culture: A serial dilution of 10 folds was performed. Bacterial suspension was diluted (10-10) with saline water and 100 μl of bacterial suspension werespread on Nutrient Agar plate and incubated for 24 hours. Bacterial colonies were isolated and grown in Nutrient Broth and nutrient agar. Other microbiological solid agar used include: Chocolate, Blood Agar, EMB, MacConkey, Simon citrate, MRS Agar. Bacteria were characterized by conventional technique by the use of morphological appearance and performance on biochemical analysis [11]. Identification of bacteria:The identification of bacteria was based on morphological characteristics and biochemical tests carried out on the isolates. Morphological characteristics observed for each bacteria colony after 24 h of growth included colony appearance; cell shape, color, optical characteristics, consistency, colonial appearance and pigmentation. Biochemical characterizations were performed according to the method of [12] Catalase test: A small quantity of 24 h old culture was transferred into a drop of 3% Hydrogen peroxide solution on a clean slide with the aid of sterile inoculating loop. Gas seen as white froth indicates the presence of catalase enzyme [13] on the isolates. DNA Extraction Processes The extraction processes was in four phase which are: Collection of cell, lyses of cell, Collection of DNA by phenol, Concentration and purification of DNA. Collection of cell: the pure colonyof the bacteria culture was inoculated into a prepared sterile nutrient broth. After growth is confirmed by the turbidity of the culture, 1.5ml of the culture was taken into a centrifuge tube and was centrifuge at 5000 rpm for 5 minutes; the supernatant layer was discarded leaving the sediment. Lyses of cell: 400 microns of lyses buffer is added to the sediment and was mixed thoroughly and allow to stand for five minutes at room temperature (25°c). 200 microns of Sodium Dodecyl Sulfate (SDS) solution was added for protein lyses and was mixed gently and incubated at 65°c for 10 minutes. Collection of DNA by phenol; 500 microns of phenol chloroform was added to the solution for the separation of DNA, it was mixed completely and centrifuge at 10,000 rpm for 10 minutes. The white pallet seen at the top of the tube after centrifugation is separated into another sterile tube and 1micron of Isopropanol is added and incubated for 1hour at -20°c for precipitation of DNA. The DNA is seen as a colorless liquid in the solution. Concentration and purification of DNA: the solution was centrifuge at 10,000 rpm for 10 minutes. The supernatant layer was discarded and the remaining DNA pellets was washed with 1micron of 17% ethanol, mixed and centrifuge at 10,000 rpm for 10 minutes. The supernatant layer was discarded and air dried. 60 micron TE. Buffer was added for further dissolving of the DNA which was later stored at -40°c until it was required for use [14]. PCR Amplification This requires the use of primers (Forward and Reverse), polymerase enzyme, a template DNA and the d pieces which includedddATP, ddGTP and ddTTP, ddNTP. All this are called the master mix. The PCR reactions consist of three main cycles. The DNA sample was heated at 940c to separate the two template of the DNA strand which was bonded by a hydrogen bond. Once both strand are separated the temperature is reduced to 570c (Annealing temperature). This temperature allows the binding of the forward and reverse primers to the template DNA. After binding the temperature is raised back to 720c which leads to the activation of polymerase enzyme and its start adding d NTPs to the DNA leading to the synthesize of new strands. The cycles were repeated several times in order to obtain millions of the copies of the target DNA [15]. Preparation of Agarose Gel One gram (1 g) of agarose for DNA was measured or 2 g of agarose powdered will be measured for PCR analysis. This done by mixing the agarose powder with 100 ml 1×TAE in a microwaveable flask and microwaved for 1-3 minutes until the agarose is completely dissolved (do not over boil the solution as some of the buffer will evaporate) and thus alter the final percentage of the agarose in the gel. Allow the agarose solution to cool down to about 50°c then after five minutes 10µL was added to EZ vision DNA stain. EZ vision binds to the DNA and allows one to easily visualize the DNA under ultra violet (UV) light. The agarose was poured into the gel tray with the well comb firmly in place and this was placed in newly poured gel at 4°c for 10-15 mins or it sit at room temperature for 20-30 mins, until it has completely solidified[16]. Loading and Running of samples on Agarose gel The agarose gel was placed into the chamber, and the process of electrophoresis commenced with running buffer introduced into the reservoir at the end of the chamber until it the buffer covered at least 2millimeter of the gel. It is advisable to place samples to be loaded in the correct order according to the lanes they are assigned to be running. When loading the samples keep the pipette tip perpendicular to the row of the wells as by supporting your accustomed hand with the second hand; this will reduce the risk of accidentally puncturing the wells with the tip. Lower the tip of the pipette until it breaks the surface of the buffer and is located just above the well. Once all the samples have been loaded it is advised to always avoid any movement of the gel chamber. This might result in the sample spilling into adjacent well. Place the lid on the gel chamber with the terminal correctly positioned to the matching electrodes on the gel chamber black to black and red to red. Remember that DNA is negatively charged hence the movement of the electric current from negatively charged to the positively charged depending on the bandwidth in Kilobytes. Once the electrode is connected to the power supply, switch ON the power supply then set the correct constant voltage (100) and stopwatch for proper time. Press the start button to begin the flow of current that will separate the DNA fragment.After few minutes the samples begins to migrate from the wells into the gel. As the DNA runs, the diaphragm moves from the negative electrode towards the positive electrode [17]. PCR mix Components and Sanger Sequencing This is made up of primers which is both Forward and Reverse, the polymerase enzyme (Taq), a template DNA and the pieces of nucleotides which include: ddNTP, ddATP, ddGTP and ddTTP. Note that the specific Primer’s sequences for bacterial identification is: 785F 5' (GGA TTA GAT ACC CTG GTA) 3', 27F 5' (AGA GTT TGA TCM TGG CTC AG) 3', 907R 5' (CCG TCA ATT CMT TTR AGT TT) 3', 1492R 5' (TAC GGY TAC CTT GTT ACG ACT T) 3' in Sanger Sequencing techniques. BLAST The resulting genomic sequence were assembled and submitted in GenBank at NCBI for assignment of accession numbers. The resultant assertion numbers were subjected to homology search by using Basic Local Alignment Search Tool (BLAST) as NCBI with the assertion number MW362290, MW362291, MW362292, MW362293, MW362294 and MW362295 respectively. Whereas, the other isolates’ accession numbers were retrieved from NCBI GenBank which are:AB 738796.1, JH792136.1, MW 015768.1 and MG745385.1.MEGA 5.2 software was used for the construction of phylogenetic tree and phylogenetic analysis. All the organisms possess 100% identities, 0% gaps and 0.0% E.value which indicated that the organisms are closely related to the existing organisms. The use of 16S rRNA is the best identification process for bacteria because 16S rRNA gene has a distinguishing size of about 500 bases until 1500bp. Rather than using 23S rRNA which is of higher variation, The 16S rRNA is adopted in prokaryotes. 18S rRNA is used for identification in Eukaryotes Results The results of both the conventional morphological and cultural identification was correlated with the molecular sequencing results. Six isolates were confirmed B. cereus species while the other four isolates were. B. wiedmannii, B. thuringiensis, B. toyonensis and B. pseudomycoides.The 16S rRNA sequence of six isolates MW 362290.1- MW362295.1 were assigned accession numbers and deposited in the GenBank while the other four sequences were aligned to those available in the NCBI database. The alignment results showed closely relatedness to LT844650.1with an identity of 100% to 92.2% as above. The six isolates of Bacillus cereus great evolutionary relatedness as shown in the phylogenetic tree constructed using MEGA X software. Results The results of both the conventional morphological and cultural identification was correlated with the molecular sequencing results. Six isolates were confirmed B. cereus species while the other four isolates were. B. wiedmannii, B. thuringiensis, B. toyonensis and B. pseudomycoides.The 16S rRNA sequence of six isolates MW 362290.1- MW362295.1 were assigned accession numbers and deposited in the GenBank while the other four sequences were aligned to those available in the NCBI database. The alignment results showed closely relatedness to LT844650.1with an identity of 100% to 92.2% as above. The six isolates of Bacillus cereus great evolutionary relatedness as shown in the phylogenetic treeconstructed using MEGA X software. Discussion The results obtained in this study is consistent with the previous studies in other countries22,23 The results of the phylogenetic analysis of the 16S rRNA isolate of in this study was similar to the housekeeping genes proposed by [18, 19]. In comparing this study with the earlier study, B. cereus group comprising other species of Bacillus was hypothesized to be considered to form a single species with different ecotypes and pathotype. This study was able to phenotypically differentiated B. thuringiensis, B. pseudomycoides, B. toyonensis, B. wiedmannii and B. cereus sensu strito. Despite differences at the colonial appearance level, the 16S rRNA sequences have homology ranging from 100% to 92% providing insufficient resolution at the species level [6, 7, 18].After analysis through various methods, the strain was identified as Gram-positive bacteria of Bacillus cereus with a homology of 99.4%. Cohan [20] demonstrated that 95–99% of the similarity of 16S rRNA gene sequence between two bacteria hints towards a similar species while >99% indicates the same bacteria.The phylogenetic tree showed that B. toyonensis, B. thuringiensis and B. wiedmanniiare the outgroups of B. cereus group while B. pseudomycoides are most closely related to B. cereus group [19, 21, 22]. Conclusion In the area of molecular epidemiology, genotypic typing method has greatly increased our ability to differentiate between micro-organisms at the intra and interspecies levels and have become an essential and powerful tool. Phenotypic method will still remain important in diagnostic microbiology and genotypic method will become increasingly popular. After analysis through various methods, the strain was identified as Gram-positive bacteria of Bacillus cereus with a homology of between 100% and 92.3%. Acknowledgments Collate acknowledgments in a separate section at the end of the article before the references, not as a footnote to the title. Use the unnumbered Acknowledgements Head style for the Acknowledgments heading. List here those individuals who provided help during the research. Conflicts of interest The Authors declare that there is no conflict of interest. References: Simpkins Meyer F.; Paarmann D.; D’Souza M.; Olson R.; Glass EM.; Kubal M.; Paczian T.; Rodriguez A.; Stevens R. Wilke A The metagenomics rast server–a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics. 2008, 9(1), 386. Segata N.; Waldron L.; Ballarini A.; Narasimhan V.; Jousson O.; Huttenhower C. Metagenomic microbial community profiling using unique clade-specific marker genes. Nature methods. 2012, 9(8), 811–814. Brady A.; Salzberg SL. Phymm and phymmbl: metagenomic phylogenetic classification with interpolated markov models. Nature Methods. 2009, 6(9), 673–676. Lindner MS.; Renard BY. Metagenomic abundance estimation and diagnostic testing on species level. Nucleic Acids Res. 2013, 41(1), 10–10. Wang A.; Ash G.J. Whole genome phylogeny of Bacillus by feature frequency profiles (FFP). Sci Rep. 2015, 5, 13644. Caroll L.M.; Kovac J.; Miller R.A.; Wiedmann M. Rapid, high-throughput identification of anthrax-causing and emetic Bacillus cereus group genome assemblies’ cereus group isolates using nucleotides sequencing data. Appli. Environ. 2017, 83: e01096-e01017 Liu Y.; Lai Q. L.; Goker M.; Meier-Kolthoff J. P.; Wang M.; Sun Y. M.; Wang L.S.; Shao Z. Genomic insights into the taxonomic status of the Bacillus cereus group. Rep. 2015, 5, 14082. Lindner MS.; Renard BY. Metagenomic profiling of known and unknown microbes with microbegps. PloS ONE. 2015, 10(2), 0117711. Versalovic J.; Schneider M.; de Bruijn FJ.; Lupski JR. Genomic fingerprinting of bacteria using repetitive sequence based PCR (rep-PCR). Meth Mol Cell Biol. 1994, 5, 25–40. Arthur Y.; Ehebauer MT.; Mukhopadhyay S.; Hasnain SE. The PE/PPE multi gene family codes for virulence factors and is a possible source of mycobacterial antigenic variation: Perhaps more? Biochimie. 2013, 94, 110–116. Jusuf, E. Culture Collection of Potential Bacillus thuringiensis Bacterial Strains Insect Killer and the Making of a Library of Toxic Protein Coding Genes. Technical Report LIPI Biotechnology Research Center. 2008. pp. 18-31. Fawole, M.O.; B.A. Oso. Characterization of Bacteria: Laboratory Manual of Microbiology. 4th Edn., Spectrum Book Ltd., Ibadan, Nigeria, 2004, pp: 24-33. Cheesbrough, M. District Laboratory Practice in Tropical Countries. 2nd Edn., Cambridge University Press, Cambridge, UK., 2006, ISBN-13: 9781139449298. Giraffa G.; Neviani E. DNA-based, cultureindependent strategies for evaluating microbial communities in food associated ecosystem. Int J Food Microbiol. 2001, 67, 19–34. Ajeet Singh. DNA Extraction from a bacterial cell. A video on Experimental Biotechnology. 2020. Quick biochemistry. A YouTube video on polymerase chain reaction. 2018. Bio-Rad laboratories. A YouTube video on loading and running of samples on Agarose gel. 2012. Saitou N. and Nei, M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Biol. Evol. 1987, 4, 406-425. Doi: 101093/oxfordjournals. Lazarte N.J.; Lopez R.P.; Ghiringhelli P.D.; Beron C.M. Bacillus wiedmannii biovar thuringiensis: A specialized Mosquitocidal pathogen with plasmid from diverse origins Genome. Evol. 2018, 10(10), 2823-2833. Doi.1093/gbe/evy211 Cohan, F.M. What are bacterial species? Rev. Microbiol. 2002, 56, 457-487 Abiola C.; Oyetayo V.O. Isolation and Biochemical Characterization of Microorganisms Associated with the Fermentation of Kersting’s Groundnut (Macrotyloma geocarpum). Research Journal of Microbiology, 2016, 11: 47- 55.DOI:10.3923/jm.2016.47.55 Adeoti O.M.; Usman T.A. Molecular Characterization of Rhizobacteria Isolates from Saki, Nigeria. Eur. Of Bio. Biotech. 2021, 2(2), 159. Doi 10.24018/ejbio.2021

Abstract PUF proteins, named for Drosophila Pumilio (PUM) and Caenorhabditis elegans fem-3-binding factor (FBF), recognize specific sequences in the mRNAs they bind and control. RNA binding by classical PUF proteins is mediated by a characteristic PUM homology domain (PUM-HD). The Puf1 and Puf2 proteins possess a distinct architecture and comprise a highly conserved subfamily among fungal species. Puf1/Puf2 proteins contain two types of RNA-binding domain: a divergent PUM-HD and an RNA recognition motif (RRM). They recognize RNAs containing UAAU motifs, often in clusters. Here, we report a crystal structure of the PUM-HD of a fungal Puf1 in complex with a dual UAAU motif RNA. Each of the two UAAU tetranucleotides are bound by a Puf1 PUM-HD forming a 2:1 protein-to-RNA complex. We also determined crystal structures of the Puf1 RRM domain that identified a dimerization interface. The PUM-HD and RRM domains act in concert to determine RNA-binding specificity: the PUM-HD dictates binding to UAAU, and dimerization of the RRM domain favors binding to dual UAAU motifs rather than a single UAAU. Cooperative action of the RRM and PUM-HD identifies a new mechanism by which multiple RNA-binding modules in a single protein collaborate to create a unique RNA-binding specificity.

Gene expression and metabolism are coupled at numerous levels. Cells must sense and respond to nutrients in their environment, and specialized cells must synthesize metabolic products required for their function. Pluripotent stem cells have the ability to differentiate into a wide variety of specialized cells. How metabolic state contributes to stem cell differentiation is not understood. In this study, we show that RNA-binding by the stem cell translation regulator Musashi-1 (MSI1) is allosterically inhibited by 18–22 carbon ω-9 monounsaturated fatty acids. The fatty acid binds to the N-terminal RNA Recognition Motif (RRM) and induces a conformational change that prevents RNA association. Musashi proteins are critical for development of the brain, blood, and epithelium. We identify stearoyl-CoA desaturase-1 as a MSI1 target, revealing a feedback loop between ω-9 fatty acid biosynthesis and MSI1 activity. We propose that other RRM proteins could act as metabolite sensors to couple gene expression changes to physiological state.

AbstractTDP-43 and hnRNPA1 contain tandemly-tethered RNA-recognition-motif (RRM) domains, which not only functionally bind an array of nucleic acids, but also participate in aggregation/fibrillation, a pathological hallmark of various human diseases including amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), alzheimer's disease (AD) and Multisystem proteinopathy (MSP). Here, by DSF, NMR and MD simulations we systematically characterized stability, ATP-binding and conformational dynamics of TDP-43 and hnRNPA1 RRM domains in both tethered and isolated forms. The results reveal three key findings: (1) upon tethering TDP-43 RRM domains become dramatically coupled and destabilized with Tm reduced to only 49 °C. (2) ATP specifically binds TDP-43 and hnRNPA1 RRM domains, in which ATP occupies the similar pockets within the conserved nucleic-acid-binding surfaces, with the affinity slightly higher to the tethered than isolated forms. (3) MD simulations indicate that the tethered RRM domains of TDP-43 and hnRNPA1 have higher conformational dynamics than the isolated forms. Two RRM domains become coupled as shown by NMR characterization and analysis of inter-domain correlation motions. The study explains the long-standing puzzle that the tethered TDP-43 RRM1–RRM2 is particularly prone to aggregation/fibrillation, and underscores the general role of ATP in inhibiting aggregation/fibrillation of RRM-containing proteins. The results also rationalize the observation that the risk of aggregation-causing diseases increases with aging.

Abstract Premature transcription termination (i.e. attenuation) is a potent gene regulatory mechanism that represses mRNA synthesis. Attenuation of RNA Polymerase II (Pol II) is more prevalent than once appreciated, targeting 10-15% of mRNA genes in yeast through higher eukaryotes, but its significance and mechanism remain obscure. In the yeast S. cerevisiae, Pol II attenuation was initially shown to rely on Nrd1-Nab3-Sen1 termination, but more recently our lab characterized a hybrid termination pathway involving Hrp1, an RNA-binding protein in the 3’-end cleavage factor (CF). One of the hybrid attenuation gene targets is DEF1, which encodes a repair protein that promotes degradation of Pol II stalled at DNA lesions. In this study we characterized the chromosomal DEF1 attenuator and the functional role of Hrp1. DEF1 attenuator mutants overexpressed Def1 mRNA and protein, exacerbated Pol II degradation, and hindered cell growth, supporting a biologically significant DEF1 attenuator function. Using an auxin-induced Hrp1 depletion system, we identified new Hrp1-dependent attenuators in MNR2, SNG1, and RAD3 genes. An hrp1-5 mutant (L205S) known to impair binding to CF protein Rna14 also disrupted attenuation, but surprisingly no widespread defect was observed for an hrp1-1 mutant (K160E) located in the RNA recognition motif (RRM). We designed a new RRM mutant (hrp1-F162W) that altered a highly conserved residue and was lethal in single copy. In a heterozygous strain, hrp1-F162W exhibited dominant-negative read through defects at multiple gene attenuators. Overall our results expand the hybrid Pol II termination pathway, confirming that Hrp1-dependent attenuation controls multiple yeast genes and may function through binding CF proteins and/or RNA.

ABSTRACT Mammalian orthoreovirus (MRV) infection induces phosphorylation of translation initiation factor eIF2α, which promotes the formation of discrete cytoplasmic inclusions, termed stress granules (SGs). SGs are emerging as a component of the innate immune response to virus infection, and modulation of SG assembly is a common mechanism employed by viruses to counter this antiviral response. We previously showed that MRV infection induces SGs early and then interferes with SG formation as infection proceeds. In this work, we found that SG-associated proteins localized to the periphery of virus-encoded cytoplasmic structures, termed virus factories (VFs), where viral transcription, translation, and replication occur. The localization of SG proteins to VFs was dependent on polysome dissociation and occurred via association of the SG effector protein, Ras-GAP SH3-binding protein 1 (G3BP1), with the MRV nonstructural protein σNS, which localizes to VFs via association with VF nucleating protein, μNS. Deletion analysis of the σNS RNA binding domain and G3BP1 RNA (RRM) and ribosomal (RGG) binding domains showed that σNS association and VF localization phenotypes of G3BP1 do not occur solely through RNA or ribosomal binding but require both the RRM and RGG domains of G3BP1 for maximal viral-factory-like structure (VFL) localization and σNS association. Coexpression of σNS and μNS resulted in disruption of normal SG puncta, and in cells lacking G3BP1, MRV replication was enhanced in a manner correlating with strain-dependent induction of host translation shutoff. These results suggest that σNS association with G3BP1 and relocalization of G3BP1 to the VF periphery play roles in SG disruption to facilitate MRV replication in the host translational shutoff environment. IMPORTANCE SGs and SG effector proteins have emerged as important, yet poorly understood, players in the host's innate immune response to virus infection. MRV infection induces SGs early during infection that are dispersed and/or prevented from forming during late stages of infection despite continued activation of the eIF2α signaling pathway. Cellular and viral components involved in disruption of SGs during late stages of MRV infection remain to be elucidated. This work provides evidence that MRV disruption of SGs may be facilitated by association of the MRV nonstructural protein σNS with the major SG effector protein G3BP1 and subsequent localization of G3BP1 and other SG-associated proteins around the peripheries of virus-encoded factories, interrupting the normal formation of SGs. Our findings also reveal the importance of G3BP1 as an inhibitor of MRV replication during infection for the first time.

AbstractThe Musashi (MSI) family of RNA-binding proteins, comprising the two homologs Musashi-1 (MSI1) and Musashi-2 (MSI2), typically regulates translation and is involved in cell proliferation and tumorigenesis. MSI proteins contain two ribonucleoprotein-like RNA-binding domains, RBD1 and RBD2, that bind single-stranded RNA motifs with a central UAG trinucleotide with high affinity and specificity. The finding that MSI also promotes the replication of Zika virus, a neurotropic Flavivirus, has triggered further investigations of the biochemical principles behind MSI–RNA interactions. However, a detailed molecular understanding of the specificity of MSI RBD1/2 interaction with RNA is still missing. Here, we performed computational studies of MSI1–RNA association complexes, investigating different RNA pentamer motifs using molecular dynamics simulations with binding free energy calculations based on the solvated interaction energy method. Simulations with Alphafold2 suggest that predicted MSI protein structures are highly similar to experimentally determined structures. The binding free energies show that two out of four RNA pentamers exhibit a considerably higher binding affinity to MSI1 RBD1 and RBD2, respectively. The obtained structural information on MSI1 RBD1 and RBD2 will be useful for a detailed functional and mechanistic understanding of this type of RNA–protein interactions.

AbstractMusashi RNA-binding proteins (MSIs) retain a pivotal role in stem cell maintenance, tumorigenesis, and nervous system development. Recently, we showed in C. elegans that Musashi (MSI-1) actively promotes forgetting upon associative learning via a 3’UTR-dependent translational expression of the Arp2/3 actin branching complex. Here, we investigated the evolutionary conserved role of MSI proteins and the effect of their pharmacological inhibition on memory. Expression of human Musashi 1 (MSI1) and Musashi 2 (MSI2) under the endogenous Musashi promoter fully rescued the phenotype of msi-1(lf) worms. Furthermore, pharmacological inhibition of human MSI1 and MSI2 activity using (-)- gossypol resulted in improved memory retention, without causing locomotor, chemotactic, or learning deficits. No drug effect was observed in msi-1(lf) treated worms. Using Western blotting and confocal microscopy, we found no changes in MSI-1 protein abundance following (-)- gossypol treatment, suggesting that Musashi gene expression remains unaltered and that the compound exerts its inhibitory effect post-translationally. Additionally, (-)- gossypol suppressed the previously seen rescue of the msi-1(lf) phenotype in worms expressing human MSI1 specifically in the AVA neuron, indicating that (-)- gossypol can regulate the Musashi pathway in a memory-related neuronal circuit in worms. Finally, treating aged worms with (-)- gossypol reversed physiological age-dependent memory decline. Taken together, our findings indicate that pharmacological inhibition of Musashi might represent a promising approach for memory modulation.

Microsatellite instability (MSI) is an important diagnostic and prognostic cancer biomarker. In colorectal, cervical, ovarian, and gastric cancers, it can guide the prescription of chemotherapy and immunotherapy. In laboratory diagnostics of susceptible tumors, MSI is routinely detected by the size of marker polymerase chain reaction products encompassing frequent microsatellite expansion regions. Alternatively, MSI status is screened indirectly by immunohistochemical interrogation of microsatellite binding proteins. RNA sequencing (RNAseq) profiling is an emerging source of data for a wide spectrum of cancer biomarkers. Recently, three RNAseq-based gene signatures were deduced for establishing MSI status in tumor samples. They had 25, 15, and 14 gene products with only one common gene. However, they were developed and tested on the incomplete literature of The Cancer Genome Atlas (TCGA) sampling and never validated experimentally on independent RNAseq samples. In this study, we, for the first time, systematically validated these three RNAseq MSI signatures on the literature colorectal cancer (CRC) (n = 619), endometrial carcinoma (n = 533), gastric cancer (n = 380), uterine carcinosarcoma (n = 55), and esophageal cancer (n = 83) samples and on the set of experimental CRC RNAseq samples (n = 23) for tumors with known MSI status. We found that all three signatures performed well with area under the curve (AUC) ranges of 0.94–1 for the experimental CRCs and 0.94–1 for the TCGA CRC, esophageal cancer, and uterine carcinosarcoma samples. However, for the TCGA endometrial carcinoma and gastric cancer samples, only two signatures were effective with AUC 0.91–0.97, whereas the third signature showed a significantly lower AUC of 0.69–0.88. Software for calculating these MSI signatures using RNAseq data is included.

AbstractHeterogeneous ribonuclear protein A18 (hnRNP A18) is an RNA binding protein (RBP) involved in the hypoxic cellular stress response and regulation of cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) expression in melanoma, breast cancer, prostate cancer, and colon cancer solid tumors. hnRNP A18 is comprised of an N-terminal structured RNA recognition motif (RMM) and a C-terminal intrinsically disordered domain (IDD). Upon cellar stressors, such as UV and hypoxia, hnRNP A18 is phosphorylated by casein kinase 2 (CK2) and glycogen synthase kinase 3β (GSK-3β). After phosphorylation, hnRNP A18 translocates from the nucleus to the cytosol where it interacts with pro-survival mRNA transcripts for proteins such as hypoxia inducible factor 1α and CTLA-4. Both the hypoxic cellular response and modulation of immune checkpoints by cancer cells promote chemoradiation resistance and metastasis. In this study, the 1 H, 13 C, and 15 N backbone and sidechain resonances of the 172 amino acid hnRNP A18 were assigned sequence-specifically and provide a framework for future NMR-based drug discovery studies toward targeting hnRNP A18. These data will also enable the investigation of the dynamic structural changes within the IDD of hnRNP A18 upon phosphorylation by CK2 and GSK-3β to provide critical insight into the structure and function of IDDs.

This study uses an in silico screening docking model to evaluate the ACE2 inhibitory activity of natural compounds and drugs. The study collected 49 compounds and evaluated the ACE2 inhibitory effect in silico. The study results show that 11 out of the 49 compounds had stronger inhibitory activity on ACE2 than MLN-4760. Lipinski’s rule of five criteria and predictive pharmacokinetic-toxicity analysis show that eight compounds including quercetin, galangin, quisinostat, fluprofylline, spirofylline, RS 504393, TNP and GNF-5 had drug-likeness. These compounds could be potential drug for the Covid-19 treatment. Keywords SARS-CoV-2S, Covid-19, ACE2, molecular docking, in silico. References [[1] C. Wang, P.W. Horby, F.G. Hayden, G.F. Gao. A novel coronavirus outbreak of global health concern. The Lancet 395(10223) (2020) 470.[2] WHO. WHO Coronavirus Disease (COVID-19) Dashboard. WHO, 2020.[3] N. Chen, M. Zhou, X. Dong, J. Qu, F. Gong, Y. Han, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. The Lancet 395(10223) (2020) 507.[4] J. Yang, Y. Zheng, X. Gou, K. Pu, Z. Chen, Q. Guo, et al. Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis. International Journal of Infectious Diseases 94 (2020) 91.[5] R. Lu, X. Zhao, J. Li, P. Niu, B. Yang, H. Wu, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. The Lancet 395(10224) (2020) 565.[6] R. Hilgenfeld. From SARS to MERS: crystallographic studies on coronaviral proteases enable antiviral drug design. The FEBS journal 281(18) (2014) 4085.[7] D. Wrapp, N. Wang, K.S. Corbett, J.A. Goldsmith, C.L. Hsieh, O. Abiona, et al. Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation. Science (New York, NY) 367(6483) (2020) 1260.[8] P.A. Rota, M.S. Oberste, S.S. Monroe, W.A. Nix, R. Campagnoli, J.P. Icenogle, et al. Characterization of a novel coronavirus associated with severe acute respiratory syndrome. Science (New York, NY) 300(5624) (2003) 1394.[9] M. Donoghue, F. Hsieh, E. Baronas, K. Godbout, M. Gosselin, N. Stagliano, et al. A novel angiotensin-converting enzyme-related carboxypeptidase (ACE2) converts angiotensin I to angiotensin 1-9. Circulation research 87(5) (2000) E1.[10] H. Zhang, Z. Kang, H. Gong, D. Xu, J. Wang, Z. Li, et al. The digestive system is a potential route of 2019-nCov infection: a bioinformatics analysis based on single-cell transcriptomes. bioRxiv (2020) 2020.01.30.927806.[11] Y. Zhao, Z. Zhao, Y. Wang, Y. Zhou, Y. Ma, W. Zuo. Single-cell RNA expression profiling of ACE2, the putative receptor of Wuhan 2019-nCov. bioRxiv (2020) 2020.01.26.919985.[12] E.I. Bahbah, A. Negida, M.S. Nabet. Purposing Saikosaponins for the treatment of COVID-19. Med Hypotheses 140 (2020) 109782.[13] I.W. Cheung, S. Nakayama, M.N. Hsu, A.G. Samaranayaka, E.C. Li-Chan. Angiotensin-I converting enzyme inhibitory activity of hydrolysates from oat (Avena sativa) proteins by in silico and in vitro analyses. Journal of agricultural and food chemistry 57(19) (2009) 9234.[14] T. Joshi, T. Joshi, P. Sharma, S. Mathpal, H. Pundir, V. Bhatt, et al. In silico screening of natural compounds against COVID-19 by targeting Mpro and ACE2 using molecular docking. European review for medical and pharmacological sciences 24(8) (2020) 4529.[15] S. Shahid, A. Kausar, M. Khalid, S. Tewari, T. Alghassab, T. Acar, et al. analysis of binding properties of angiotensin-converting enzyme 2 through in silico molecular docking, 2018.[16] K. Teralı, B. Baddal, H.O. Gülcan. Prioritizing potential ACE2 inhibitors in the COVID-19 pandemic: Insights from a molecular mechanics-assisted structure-based virtual screening experiment. J Mol Graph Model 100 (2020) 107697.[17] M. Muchtaridi, M. Fauzi, N.K. Khairul Ikram, A. Mohd Gazzali, H.A. Wahab. Natural Flavonoids as Potential Angiotensin-Converting Enzyme 2 Inhibitors for Anti-SARS-CoV-2. Molecules 25(17) (2020) 3980.[18] M.J. Huentelman, J. Zubcevic, J.A. Hernández Prada, X. Xiao, D.S. Dimitrov, M.K. Raizada, et al. Structure-based discovery of a novel angiotensin-converting enzyme 2 inhibitor. Hypertension (Dallas, Tex : 1979) 44(6) (2004) 903.[19] S. Choudhary, Y.S. Malik, S. Tomar. Identification of SARS-CoV-2 Cell Entry Inhibitors by Drug Repurposing Using in silico Structure-Based Virtual Screening Approach. Front Immunol 11((2020) 1664.[20] C.A. Lipinski. Lead-and drug-like compounds: the rule-of-five revolution. Drug Discovery Today: Technologies 1(4) (2004) 337.[21] B. Jayaram, T. Singh, G. Mukherjee, A. Mathur, S. Shekhar, V. Shekhar, Eds. Sanjeevini: a freely accessible web-server for target directed lead molecule discovery. Proceedings of the BMC bioinformatics; 2012. Springer (Year).[22] D.E. Pires, T.L. Blundell, D.B. Ascher. pkCSM: predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures. Journal of medicinal chemistry 58(9) (2015) 4066.[23] P. Towler, B. Staker, S.G. Prasad, S. Menon, J. Tang, T. Parsons, et al. ACE2 X-ray structures reveal a large hinge-bending motion important for inhibitor binding and catalysis. The Journal of biological chemistry 279(17) (2004) 17996.[24] N.A. Dales, A.E. Gould, J.A. Brown, E.F. Calderwood, B. Guan, C.A. Minor, et al. Substrate-based design of the first class of angiotensin-converting enzyme-related carboxypeptidase (ACE2) inhibitors. Journal of the American Chemical Society 124(40) (2002) 11852.[25] P. Pandey, J.S. Rane, A. Chatterjee, A. Kumar, R. Khan, A. Prakash, et al. Targeting SARS-CoV-2 spike protein of COVID-19 with naturally occurring phytochemicals: an in silico study for drug development. Journal of Biomolecular Structure and Dynamics (2020) 1.[26] C.A. Lipinski. Lead- and drug-like compounds: the rule-of-five revolution. Drug discovery today Technologies 1(4) (2004) 337.[27] R.O. Barros, F.L. Junior, W.S. Pereira, N.M. Oliveira, R.M. Ramos. Interaction of drug candidates with various SARS-CoV-2 receptors: An in silico study to combat COVID-19. Journal of Proteome Research (2020).

Malignant hyperthermia (MH) is a clinical response happened to patient who is sensitive with inhaled anesthesia drug that could cause suddently death. Many previous studies showed that malignant hyperthermia strongly related to genetic background of patients including RYR1, CACNA1S or STAC3 gene polymorphisms. With the development of high technology such as next generation sequencing, scientists found that 37 to 86 percents of MH cases had RYR1 mutations and approximately 1 percent of those had CACNA1S mutations. Gene analysis testing was recommended to apply for patient with MH medical history or MH patient’s family relations. Keywords Malignant hyperthermia, inhaled anesthesia, RYR1, CACNA1S, STAC3. References [1] G. Torri, Inhalation anesthetics: a review, Minerva Anestesiologica 76 (2010) 215–228. [2] N. Kassiri, S. Ardehali, F. Rashidi, S. Hashemian, Inhalational anesthetics agents: The pharmacokinetic, pharmacodynamics, and their effects on human body, Biomed. Biotechnol. Res. J. BBRJ 2 (2018) 173. https://doi.org/10.4103/bbrj.bbrj_6618.[3] H. Rosenberg, N. Sambuughin, S. Riazi, R. Dirksen, Malignant Hyperthermia Susceptibility, in: M.P. Adam, H.H. Ardinger, R.A. Pagon, S.E. Wallace, L.J. Bean, K. Stephens, A. Amemiya (Eds.), GeneReviews, University of Washington, Seattle, Seattle (WA), 19932020. http://www.ncbi.nlm.nih.gov/books/NBK1146/ (accessed February 2, 2020).[4] H. Rosenberg, N. Pollock, A. Schiemann, T. Bulger, K. Stowell, Malignant hyperthermia: a review, Orphanet J. Rare Dis 10 (2015) 93. https://doi.org/10.1186/s13023-015-0310-1.[5] D. Carpenter, C. Ringrose, V. Leo, A. Morris, R.L. Robinson, P.J. Halsall, P.M. Hopkins, M.-A. Shaw, The role of CACNA1S in predisposition to malignant hyperthermia, BMC Med. Genet 10 (2009) 104. https://doi.org/10.1186/1471-2350-10-104.[6] S. Riazi, N. Kraeva, P.M. Hopkins, Updated guide for the management of malignant hyperthermia, Can. J. Anaesth. J. Can. Anesth 65 (2018) 709–721. https://doi.org/10.1007/s12630-018-1108-0.[7] S. Riazi, N. Kraeva, P.M. Hopkins, Malignant Hyperthermia in the Post-Genomics Era: New Perspectives on an Old Concept, Anesthesiology 128 (2018) 168–180. https://doi.org/10.1097/ALN.0000000000001878.[8] [D.M. Miller, C. Daly, E.M. Aboelsaod, L. Gardner, S.J. Hobson, K. Riasat, S. Shepherd, R.L. Robinson, J.G. Bilmen, P.K. Gupta, M.-A. Shaw, P.M. Hopkins, Genetic epidemiology of malignant hyperthermia in the UK, BJA Br. J. Anaesth 121 (2018) 944–952. https://doi.org/10.1016/j.bja.2018.06.028.[9] T.A. Beam, E.F. Loudermilk, D.F. Kisor, Pharmacogenetics and pathophysiology of CACNA1S mutations in malignant hyperthermia, Physiol. Genomics 49 (2017) 81–87. https://doi.org/10.1152/physiolgenomics.00126.2016.[10] I.T. Zaharieva, A. Sarkozy, P. Munot, A. Manzur, G. O’Grady, J. Rendu, E. Malfatti, H. Amthor, L. Servais, J.A. Urtizberea, O.A. Neto, E. Zanoteli, S. Donkervoort, J. Taylor, J. Dixon, G. Poke, A.R. Foley, C. Holmes, G. Williams, M. Holder, S. Yum, L. Medne, S. Quijano-Roy, N.B. Romero, J. Fauré, L. Feng, L. Bastaki, M.R. Davis, R. Phadke, C.A. Sewry, C.G. Bönnemann, H. Jungbluth, C. Bachmann, S. Treves, F. Muntoni, STAC3 variants cause a congenital myopathy with distinctive dysmorphic features and malignant hyperthermia susceptibility, Hum. Mutat 39 (2018) 1980–1994. https://doi.org/10.1002/humu.23635.[11] A.F. Dulhunty, The voltage-activation of contraction in skeletal muscle, Prog. Biophys. Mol. Biol 57 (1992) 181–223. https://doi.org/10.1016/0079-6107(92)90024-Z.[12] C. Franzini-Armstrong, A.O. Jorgensen, Structure and Development of E-C Coupling Units in Skeletal Muscle, Annu. Rev. Physiol 56 (1994) 509–534. https://doi.org/10.1146/annurev.ph.56.030194.002453.[13] D.H. MacLennan, M. Abu-Abed, C. Kang, Structure-function relationships in Ca(2+) cycling proteins, J. Mol. Cell. Cardiol 34 (2002) 897–918. https://doi.org/10.1006/jmcc.2002.2031.[14] H. Rosenberg, M. Davis, D. James, N. Pollock, K. Stowell, Malignant hyperthermia, Orphanet J. Rare Dis 2 (2007) 21. https://doi.org/10.1186/1750-1172-2-21.[15] S.M. Karan, F. Crowl, S.M. Muldoon, Malignant hyperthermia masked by capnographic monitoring, Anesth. Analg 78 (1994) 590–592. https://doi.org/10.1213/00000539-199403000-00029.[16] M.G. Larach, G.A. Gronert, G.C. Allen, B.W. Brandom, E.B. Lehman, Clinical presentation, treatment, and complications of malignant hyperthermia in North America from 1987 to 2006, Anesth. Analg 110 (2010) 498–507. https://doi.org/10.1213/ANE.0b013e3181c6b9b2.[17] M.G. Larach, A.R. Localio, G.C. Allen, M.A. Denborough, F.R. Ellis, G.A. Gronert, R.F. Kaplan, S.M. Muldoon, T.E. Nelson, H. Ording, H. Rosenberg, B.E. Waud, D.J. Wedel, A Clinical Grading Scale to Predict Malignant Hyperthermia Susceptibility, Anesthesiology 80 (1994) 771–779. https://doi.org/10.1097/00000542-199404000-00008.[18] D. Schneiderbanger, S. Johannsen, N. Roewer, F. Schuster, Management of malignant hyperthermia: diagnosis and treatment, Ther. Clin. Risk Manag 10 (2014) 355–362. https://doi.org/10.2147/TCRM.S47632.[19] R. Robinson, D. Carpenter, M.-A. Shaw, J. Halsall, P. Hopkins, Mutations in RYR1 in malignant hyperthermia and central core disease, Hum. Mutat 27 (2006) 977–989. https://doi.org/10.1002/humu.20356.[20] M.L. Alvarellos, R.M. Krauss, R.A. Wilke, R.B. Altman, T.E. Klein, PharmGKB summary: very important pharmacogene information for RYR1, Pharmacogenet. Genomics 26 (2016) 138–144. https://doi.org/10.1097/FPC.0000000000000198.[21] A. Merritt, P. Booms, M.-A. Shaw, D.M. Miller, C. Daly, J.G. Bilmen, K.M. Stowell, P.D. Allen, D.S. Steele, P.M. Hopkins, Assessing the pathogenicity of RYR1 variants in malignant hyperthermia, BJA Br. J. Anaesth 118 (2017) 533–543. https://doi.org/10.1093/bja/aex042.[22] P.M. Hopkins, H. Rüffert, M.M. Snoeck, T. Girard, K.P.E. Glahn, F.R. Ellis, C.R. Müller, A. Urwyler, European Malignant Hyperthermia Group, European Malignant Hyperthermia Group guidelines for investigation of malignant hyperthermia susceptibility, Br. J. Anaesth 115 (2015) 531–539. https://doi.org/10.1093/bja/aev225.[23] N.T. Thuy, L.N. Thanh, N.T.T. Mau, N.H. Hoang, N.T.K. Lien, D.D. Long, N.T. Bình, D.A. Tien, N.C. Huu, N.T. Hieu, P.T.H. Nhung, V.T. Thom, Whole exome sequencing revealed a pathogenic variant in a gene related to malignant hyperthermia in a Vietnamese cardiac surgical patient: A case report, Ann. Med. Surg 48 (2019) 88–90. https://doi.org/10.1016/j.amsu.2019.10.030.[24] B. Neuhuber, U. Gerster, F. Döring, H. Glossmann, T. Tanabe, B.E. Flucher, Association of calcium channel α1S and β1a subunits is required for the targeting of β1a but not of α1S into skeletal muscle triads, Proc. Natl. Acad. Sci. U. S. A 95 (1998) 5015–5020. https://doi.org/10.1073/pnas.95.9.5015.[25] M. Whirl-Carrillo, E.M. McDonagh, J.M. Hebert, L. Gong, K. Sangkuhl, C.F. Thorn, R.B. Altman, T.E. Klein, Pharmacogenomics Knowledge for Personalized Medicine, Clin. Pharmacol. Ther 92 (2012) 414–417. https://doi.org/10.1038/clpt.2012.96.[26] N. Monnier, V. Procaccio, P. Stieglitz, J. Lunardi, Malignant-hyperthermia susceptibility is associated with a mutation of the alpha 1-subunit of the human dihydropyridine-sensitive L-type voltage-dependent calcium-channel receptor in skeletal muscle, Am. J. Hum. Genet 60 (1997) 1316–1325 . https://doi.org/10.1086/515454.[27] S.L. Stewart, K. Hogan, H. Rosenberg, J.E. Fletcher, Identification of the Arg1086His mutation in the alpha subunit of the voltage-dependent calcium channel (CACNA1S) in a North American family with malignant hyperthermia, Clin. Genet 59 (2001) 178–184. https://doi.org/10.1034/j.1399 0004.2001.590306.x.[28] P.J. Toppin, T.T. Chandy, A. Ghanekar, N. Kraeva, W.S. Beattie, S. Riazi, A report of fulminant malignant hyperthermia in a patient with a novel mutation of the CACNA1S gene, Can. J. Anaesth. J. Can. Anesth 57 (2010) 689–693. https://doi.org/10.1007/s12630-010-9314-4.[29] E.J. Horstick, J.W. Linsley, J.J. Dowling, M.A. Hauser, K.K. McDonald, A. Ashley-Koch, L. Saint-Amant, A. Satish, W.W. Cui, W. Zhou, S.M. Sprague, D.S. Stamm, C.M. Powell, M.C. Speer, C. Franzini-Armstrong, H. Hirata, J.Y. Kuwada, Stac3 is a component of the excitation-contraction coupling machinery and mutated in Native American myopathy, Nat. Commun 4 (2013) 1952. https://doi.org/10.1038/ncomms2952.[30] D.S. Stamm, A.S. Aylsworth, J.M. Stajich, S.G. Kahler, L.B. Thorne, M.C. Speer, C.M. Powell, Native American myopathy: Congenital myopathy with cleft palate, skeletal anomalies, and susceptibility to malignant hyperthermia, Am. J. Med. Genet. A 146A (2008) 1832–1841. https://doi.org/10.1002/ajmg.a.32370.[31] A. Polster, B.R. Nelson, S. Papadopoulos, E.N. Olson, K.G. Beam, Stac proteins associate with the critical domain for excitation–contraction coupling in the II–III loop of CaV1.1, J. Gen. Physiol 150 (2018) 613–624. https://doi.org/10.1085/jgp.201711917.[32] S.M. Wong King Yuen, M. Campiglio, C.-C. Tung, B.E. Flucher, F. Van Petegem, Structural insights into binding of STAC proteins to voltage-gated calcium channels, Proc. Natl. Acad. Sci 114 (2017) E9520–E9528. https://doi.org/10.1073/pnas.1708852114.[33] M. Grabner, R.T. Dirksen, N. Suda, K.G. Beam, The II-III loop of the skeletal muscle dihydropyridine receptor is responsible for the Bi-directional coupling with the ryanodine receptor, J. Biol. Chem 274 (1999) 21913–21919. https://doi.org/10.1074/jbc.274.31.21913.[34] J. Nakai, T. Tanabe, T. Konno, B. Adams, K.G. Beam, Localization in the II-III loop of the dihydropyridine receptor of a sequence critical for excitation-contraction coupling, J. Biol. Chem 273 (1998) 24983–24986. https://doi.org/10.1074/jbc.273.39.24983.[35] C.J. Morton, I.D. Campbell, SH3 domains. Molecular “Velcro,” Curr. Biol. CB 4 (1994) 615–617. https://doi.org/10.1016/s0960-9822(00)00134-2.[36] A. Zafra-Ruano, I. Luque, Interfacial water molecules in SH3 interactions: Getting the full picture on polyproline recognition by protein-protein interaction domains, FEBS Lett 586 (2012) 2619–2630. https://doi.org/10.1016/j.febslet.2012.04.057.