RESUMO
Cryogenic electron tomography (cryo-ET) visualizes the 3D spatial distribution of macromolecules at nanometer resolution inside native cells. However, automated identification of macromolecules inside cellular tomograms is challenged by noise and reconstruction artifacts, as well as the presence of many molecular species in the crowded volumes. Here, we present DeepFinder, a computational procedure that uses artificial neural networks to simultaneously localize multiple classes of macromolecules. Once trained, the inference stage of DeepFinder is faster than template matching and performs better than other competitive deep learning methods at identifying macromolecules of various sizes in both synthetic and experimental datasets. On cellular cryo-ET data, DeepFinder localized membrane-bound and cytosolic ribosomes (roughly 3.2 MDa), ribulose 1,5-bisphosphate carboxylase-oxygenase (roughly 560 kDa soluble complex) and photosystem II (roughly 550 kDa membrane complex) with an accuracy comparable to expert-supervised ground truth annotations. DeepFinder is therefore a promising algorithm for the semiautomated analysis of a wide range of molecular targets in cellular tomograms.
Assuntos
Algoritmos , Microscopia Crioeletrônica/métodos , Aprendizado Profundo , Tomografia com Microscopia Eletrônica/métodos , Processamento de Imagem Assistida por Computador/métodos , Substâncias Macromoleculares/química , Redes Neurais de Computação , Chlamydomonas reinhardtii/metabolismo , Complexo de Proteína do Fotossistema II/química , Ribossomos/química , Ribulose-Bifosfato Carboxilase/químicaRESUMO
The structural modeling of a macromolecular machine is like a "Lego" approach that is challenged when blocks, like proteins imported from the Protein Data Bank, are to be assembled with an element adopting a serpentine shape, such as DNA templates. DNA must then be built ex nihilo, but modeling approaches are either not user-friendly or very long and fastidious. In this method chapter we show how to use GraphiteLifeExplorer, a software with a simple graphical user interface that enables the sketching of free forms of DNA, of any length, at the atomic scale, as fast as drawing a line on a sheet of paper. We took as an example the nucleoprotein complex of DNA gyrase, a bacterial topoisomerase whose structure has been determined using cryo-electron microscopy (Cryo-EM). Using GraphiteLifeExplorer, we could model in one go a 155 bp long and twisted DNA duplex that wraps around DNA gyrase in the cryo-EM map, improving the quality and interpretation of the final model compared to the initially published data.
Assuntos
DNA Girase/química , DNA Girase/metabolismo , DNA Bacteriano/metabolismo , Microscopia Crioeletrônica , DNA Bacteriano/química , Bases de Dados de Proteínas , Substâncias Macromoleculares/química , Substâncias Macromoleculares/metabolismo , Modelos Moleculares , Conformação Proteica , SoftwareRESUMO
The GraphiteLifeExplorer tool enables biologists to reconstruct 3D cellular complexes built from proteins and DNA molecules. Models of DNA molecules can be drawn in an intuitive way and assembled to proteins or others globular structures. Real time navigation and immersion offer a unique view to the reconstructed biological machinery.
Assuntos
DNA Bacteriano/química , Proteínas de Escherichia coli/química , Escherichia coli/química , Modelos Moleculares , Software , Algoritmos , Simulação por Computador , Conformação MolecularRESUMO
The ternary complex comprising MutS, MutL, and DNA is a key intermediate in DNA mismatch repair. We used chemical cross-linking and fluorescence resonance energy transfer (FRET) to study the interaction between MutS and MutL and to shed light onto the structure of this complex. Via chemical cross-linking, we could stabilize this dynamic complex and identify the structural features of key events in DNA mismatch repair. We could show that in the complex between MutS and MutL the mismatch-binding and connector domains of MutS are in proximity to the N-terminal ATPase domain of MutL. The DNA- and nucleotide-dependent complex formation could be monitored by FRET using single cysteine variants labeled in the connector domain of MutS and the transducer domain of MutL, respectively. In addition, we could trap MutS after an ATP-induced conformational change by an intramolecular cross-link between Cys-93 of the mismatch-binding domain and Cys-239 of the connector domain.
Assuntos
Adenosina Trifosfatases/química , Reparo de Erro de Pareamento de DNA , Proteínas de Escherichia coli/química , Escherichia coli/enzimologia , Regulação Bacteriana da Expressão Gênica , Proteína MutS de Ligação de DNA com Erro de Pareamento/química , Trifosfato de Adenosina/química , Reagentes de Ligações Cruzadas/química , Reagentes de Ligações Cruzadas/farmacologia , Cisteína/química , Reparo do DNA , Enzimas Reparadoras do DNA/metabolismo , Proteínas de Ligação a DNA/metabolismo , Endodesoxirribonucleases/metabolismo , Proteínas de Escherichia coli/metabolismo , Transferência Ressonante de Energia de Fluorescência/métodos , Proteínas MutL , Mutagênese Sítio-Dirigida , Conformação Proteica , Estrutura Terciária de Proteína , UltracentrifugaçãoRESUMO
Formerly regarded as small 'bags' of nucleic acids with randomly diffusing enzymes, bacteria are organized by a sophisticated and tightly regulated molecular machinery. Here, we review qualitative and quantitative data on the intracellular organization of bacteria and provide a detailed inventory of macromolecular structures such as the divisome, the degradosome and the bacterial 'nucleolus'. We discuss how these metabolically active structures manage the spatial organization of the cell and how macromolecular crowding influences them. We present for the first time a visualization program, lifeexplorer, that can be used to study the interplay between metabolism and spatial organization of a prokaryotic cell.
