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Institute
- Biochemie, Chemie und Pharmazie (281)
- Zentrum für Biomolekulare Magnetische Resonanz (BMRZ) (30)
- Medizin (26)
- Buchmann Institut für Molekulare Lebenswissenschaften (BMLS) (22)
- Biowissenschaften (15)
- MPI für Biophysik (9)
- Physik (7)
- Zentrum für Arzneimittelforschung, Entwicklung und Sicherheit (ZAFES) (5)
- Exzellenzcluster Makromolekulare Komplexe (3)
- MPI für Hirnforschung (2)
Transfer RNAs (tRNAs) are highly structured non-coding RNAs which play key roles in translation and cellular homeostasis. tRNAs are initially transcribed as precursor molecules and mature by tightly controlled, multistep processes that involve the removal of flanking and intervening sequences, over 100 base modifications, addition of non-templated nucleotides and aminoacylation. These molecular events are intertwined with the nucleocy- toplasmic shuttling of tRNAs to make them available at translating ribosomes. Defects in tRNA processing are linked to the development of neurodegenerative disorders. Here, we summarize structural aspects of tRNA processing steps with a special emphasis on intron-containing tRNA splicing involving tRNA splicing endonuclease and ligase. Their role in neurological pathologies will be discussed. Identification of novel RNA substrates of the tRNA splicing machinery has uncovered functions unrelated to tRNA processing. Future structural and biochemical studies will unravel their mechanistic underpinnings and deepen our understanding of neurological diseases.
The KMT2A (MLL) gene rearrangements (KMT2A-r) are associated with a diverse spectrum of acute leukemias. Although most KMT2A-r are restricted to nine partner genes, we have recently revealed that KMT2A-USP2 fusions are often missed during FISH screening of these genetic alterations. Therefore, complementary methods are important for appropriate detection of any KMT2A-r. Here we use a machine learning model to unravel the most appropriate markers for prediction of KMT2A-r in various types of acute leukemia. A Random Forest and LightGBM classifier was trained to predict KMT2A-r in patients with acute leukemia. Our results revealed a set of 20 genes capable of accurately estimating KMT2A-r. The SKIDA1 (AUC: 0.839; CI: 0.799–0.879) and LAMP5 (AUC: 0.746; CI: 0.685–0.806) overexpression were the better markers associated with KMT2A-r compared to CSPG4 (also named NG2; AUC: 0.722; CI: 0.659–0.784), regardless of the type of acute leukemia. Of importance, high expression levels of LAMP5 estimated the occurrence of all KMT2A-USP2 fusions. Also, we performed drug sensitivity analysis using IC50 data from 345 drugs available in the GDSC database to identify which ones could be used to treat KMT2A-r leukemia. We observed that KMT2A-r cell lines were more sensitive to 5-Fluorouracil (5FU), Gemcitabine (both antimetabolite chemotherapy drugs), WHI-P97 (JAK-3 inhibitor), Foretinib (MET/VEGFR inhibitor), SNX-2112 (Hsp90 inhibitor), AZD6482 (PI3Kβ inhibitor), KU-60019 (ATM kinase inhibitor), and Pevonedistat (NEDD8-activating enzyme (NAE) inhibitor). Moreover, IC50 data from analyses of ex-vivo drug sensitivity to small-molecule inhibitors reveals that Foretinib is a promising drug option for AML patients carrying FLT3 activating mutations. Thus, we provide novel and accurate options for the diagnostic screening and therapy of KMT2A-r leukemia, regardless of leukemia subtype.
Meat adulteration is a global problem which undermines market fairness and harms people with allergies or certain religious beliefs. In this study, a novel framework in which a one-dimensional convolutional neural network (1DCNN) serves as a backbone and a random forest regressor (RFR) serves as a regressor, named 1DCNN-RFR, is proposed for the quantitative detection of beef adulterated with pork using electronic nose (E-nose) data. The 1DCNN backbone extracted a sufficient number of features from a multichannel input matrix converted from the raw E-nose data. The RFR improved the regression performance due to its strong prediction ability. The effectiveness of the 1DCNN-RFR framework was verified by comparing it with four other models (support vector regression model (SVR), RFR, backpropagation neural network (BPNN), and 1DCNN). The proposed 1DCNN-RFR framework performed best in the quantitative detection of beef adulterated with pork. This study indicated that the proposed 1DCNN-RFR framework could be used as an effective tool for the quantitative detection of meat adulteration.
The current pandemic situation caused by the Betacoronavirus SARS-CoV-2 (SCoV2) highlights the need for coordinated research to combat COVID-19. A particularly important aspect is the development of medication. In addition to viral proteins, structured RNA elements represent a potent alternative as drug targets. The search for drugs that target RNA requires their high-resolution structural characterization. Using nuclear magnetic resonance (NMR) spectroscopy, a worldwide consortium of NMR researchers aims to characterize potential RNA drug targets of SCoV2. Here, we report the characterization of 15 conserved RNA elements located at the 5′ end, the ribosomal frameshift segment and the 3′-untranslated region (3′-UTR) of the SCoV2 genome, their large-scale production and NMR-based secondary structure determination. The NMR data are corroborated with secondary structure probing by DMS footprinting experiments. The close agreement of NMR secondary structure determination of isolated RNA elements with DMS footprinting and NMR performed on larger RNA regions shows that the secondary structure elements fold independently. The NMR data reported here provide the basis for NMR investigations of RNA function, RNA interactions with viral and host proteins and screening campaigns to identify potential RNA binders for pharmaceutical intervention.
Despite a high clinical need for the treatment of colorectal carcinoma (CRC) as the second leading cause of cancer-related deaths, targeted therapies are still limited. The multifunctional enzyme Transglutaminase 2 (TGM2), which harbors transamidation and GTPase activity, has been implicated in the development and progression of different types of human cancers. However, the mechanism and role of TGM2 in colorectal cancer are poorly understood. Here, we present TGM2 as a promising drug target.
In primary patient material of CRC patients, we detected an increased expression and enzymatic activity of TGM2 in colon cancer tissue in comparison to matched normal colon mucosa cells. The genetic ablation of TGM2 in CRC cell lines using shRNAs or CRISPR/Cas9 inhibited cell expansion and tumorsphere formation. In vivo, tumor initiation and growth were reduced upon genetic knockdown of TGM2 in xenotransplantations. TGM2 ablation led to the induction of Caspase-3-driven apoptosis in CRC cells. Functional rescue experiments with TGM2 variants revealed that the transamidation activity is critical for the pro-survival function of TGM2. Transcriptomic and protein–protein interaction analyses applying various methods including super-resolution and time-lapse microscopy showed that TGM2 directly binds to the tumor suppressor p53, leading to its inactivation and escape of apoptosis induction.
We demonstrate here that TGM2 is an essential survival factor in CRC, highlighting the therapeutic potential of TGM2 inhibitors in CRC patients with high TGM2 expression. The inactivation of p53 by TGM2 binding indicates a general anti-apoptotic function, which may be relevant in cancers beyond CRC.
Fluorescently labeled nanoparticles are widely used for evaluating their distribution in the biological environment. However, dye leakage can lead to misinterpretations of the nanoparticles’ biodistribution. To better understand the interactions of dyes and nanoparticles and their biological environment, we explored PLGA nanoparticles labeled with four widely used dyes encapsulated (coumarin 6, rhodamine 123, DiI) or bound covalently to the polymer (Cy5.5.). The DiI label was stable in both aqueous and lipophilic environments, whereas the quick release of coumarin 6 was observed in model media containing albumin (42%) or liposomes (62%), which could be explained by the different affinity of these dyes to the polymer and lipophilic structures and which we also confirmed by computational modeling (log PDPPC/PLGA: DiI—2.3, Cou6—0.7). The importance of these factors was demonstrated by in vivo neuroimaging (ICON) of the rat retina using double-labeled Cy5.5/Cou6-nanoparticles: encapsulated Cou6 quickly leaked into the tissue, whereas the stably bound Cy.5.5 label remained associated with the vessels. This observation is a good example of the possible misinterpretation of imaging results because the coumarin 6 distribution creates the impression that nanoparticles effectively crossed the blood–retina barrier, whereas in fact no signal from the core material was found beyond the blood vessels.
The ribosomal S1 protein (rS1) is indispensable for translation initiation in Gram-negative bacteria. rS1 is a multidomain protein that acts as an RNA chaperone and ensures that mRNAs can bind the ribosome in a single-stranded conformation, which could be related to fast recognition. Although many ribosome structures were solved in recent years, a high-resolution structure of a two-domain mRNA-binding competent rS1 construct is not yet available. Here, we present the NMR solution structure of the minimal mRNA-binding fragment of Vibrio Vulnificus rS1 containing the domains D3 and D4. Both domains are homologues and adapt an oligonucleotide-binding fold (OB fold) motif. NMR titration experiments reveal that recognition of miscellaneous mRNAs occurs via a continuous interaction surface to one side of these structurally linked domains. Using a novel paramagnetic relaxation enhancement (PRE) approach and exploring different spin-labeling positions within RNA, we were able to track the location and determine the orientation of the RNA in the rS1–D34 bound form. Our investigations show that paramagnetically labeled RNAs, spiked into unmodified RNA, can be used as a molecular ruler to provide structural information on protein-RNA complexes. The dynamic interaction occurs on a defined binding groove spanning both domains with identical β2-β3-β5 interfaces. Evidently, the 3′-ends of the cis-acting RNAs are positioned in the direction of the N-terminus of the rS1 protein, thus towards the 30S binding site and adopt a conformation required for translation initiation.
Copper perchlorophthalocyanine (CuPcCl16, CuC32N8Cl16, Pigment Green 7) is one of the commercially most important green pigments. The compound is a nanocrystalline fully insoluble powder. Its crystal structure was first addressed by electron diffraction in 1972 [Uyeda et al. (1972). J. Appl. Phys. 43, 5181–5189]. Despite the commercial importance of the compound, the crystal structure remained undetermined until now. Using a special vacuum sublimation technique, micron-sized crystals could be obtained. Three-dimensional electron diffraction (3D ED) data were collected in two ways: (i) in static geometry using a combined stage-tilt/beam-tilt collection scheme and (ii) in continuous rotation mode. Both types of data allowed the crystal structure to be solved by direct methods. The structure was refined kinematically with anisotropic displacement parameters for all atoms. Due to the pronounced crystal mosaicity, a dynamic refinement was not feasible. The unit-cell parameters were verified by Rietveld refinement from powder X-ray diffraction data. The crystal structure was validated by many-body dispersion density functional theory (DFT) calculations. CuPcCl16 crystallizes in the space group C2/m (Z = 2), with the molecules arranged in layers. The structure agrees with that proposed in 1972.