PubMed Health⌕ Search

PubMed · 16430129

S-layers as patterning elements for application in nanobiotechnology.

Abstract

Two-dimensional bacterial cell surface layer protein crystals (S-layers) are the most commonly observed cell surface structure in bacteria and archaea. Isolated S-layer proteins have the intrinsic tendency to self-assemble into crystalline arrays in suspension and on various interfaces. Basic research on the structure, genetics, chemistry, morphogenesis and function of S-layers has led to a broad spectrum of applications in nanotechnology and biomimetics. The possibility to change the properties of S-layer proteins by genetic engineering opens new ways for tuning their functional and structural features. Functionalized S-layer proteins that maintain their ability to self-assemble have led to new affinity matrices, diagnostic tools, vaccines or biocompatible surfaces, as well as to biological templating or specific biomineralisation strategies at surfaces.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Margit Sára, Dietmar Pum, Bernhard Schuster, Uwe B Sleytr. 2005. S-layers as patterning elements for application in nanobiotechnology.. https://doi.org/10.1166/jnn.2005.502

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Prediction of bacterial protein-compound interactions with only positive samples.

MOTIVATION: Prediction of Compound-Protein Interactions (CPI) in bacteria is crucial to advance various pharmaceutical and chemical engineering fields, including biocatalysis, drug discovery, and industrial processing. However, current CPI models cannot be applied for bacterial CPI prediction due to the lack of curated negative interaction samples. RESULTS: We propose a novel Positive-Unlabeled (PU) learning framework, named BIN-PU, to address this limitation. BIN-PU generates pseudo positive and negative labels from known positive interaction data, enabling effective training of deep learning models for CPI prediction. We also propose a weighted positive loss function that weights to truly positive samples. We have validated BIN-PU coupled with multiple CPI backbone models, comparing the performance with the existing PU models using bacterial cytochrome P450 (CYP) data. Extensive experiments demonstrate the superiority of BIN-PU over the benchmark models in predicting CPIs with only truly positive samples. Furthermore, we have validated BIN-PU on additional bacterial proteins obtained from literature review, human CYP datasets, and uncurated data for its reproducibility. We have also validated the CPI prediction for the uncurated CYP data with biological and biophysical experiments. BIN-PU represents a significant advancement in CPI prediction for bacterial proteins, opening new possibilities for improving predictive models in related biological interaction tasks. AVAILABILITY AND IMPLEMENTATION: The source code and data are available at https://github.com/datax-lab/CYP.

Bacterial Proteins↗

ComFB, a widespread family of c-di-NMP receptor proteins.

Cyclic dimeric-GMP (c-di-GMP) is a ubiquitous bacterial second messenger that regulates a variety of cellular processes, including motility, biofilm formation, secretion, cell cycle progression, and development, and also contributes to the virulence of many bacterial pathogens. While the genes encoding c-di-GMP cyclases and hydrolases are readily identifiable in microbial genomes, known c-di-GMP receptor domains are quite few, with only PilZ and MshEN broadly distributed across bacterial phyla. Recently, a new c-di-GMP receptor, named CdgR or ComFB, has been identified in cyanobacteria and shown to regulate cell size and natural competence. We demonstrated that CdgR proteins exhibit sequence and structural similarity to the Bacillus subtilis late competence development protein ComFB, a conserved protein of unknown function associated with bacterial competence. This prompted us to hypothesize that ComFB and ComFB-like proteins could also serve as c-di-GMP receptors. Here, we comprehensively investigated the ComFB protein family and demonstrated that ComFB proteins are evolutionarily widespread among bacteria and function as a novel family of c-di-GMP receptors. We showed that ComFB proteins from Gram-positive bacteria (B. subtilis, Thermoanaerobacter brockii) and Gram-negative pathogens (Vibrio cholerae, Treponema denticola) bind c-di-GMP with high affinity. Several ComFB proteins also bind cyclic di-adenosine monophosphate (c-di-AMP), suggesting that ComFB represents a widely distributed bacterial protein family with dual specificity for c-di-GMP and c-di-AMP. Our physiological studies further showed that ComFB plays vital roles in controlling motility in a c-di-GMP-dependent manner in two phylogenetically distant bacteria, B. subtilis and the gram-negative Shewanella oneidensis, attesting to the biological relevance of ComFB as a c-di-GMP binding protein.

Bacterial Proteins↗

Dynamic structural determinants in bacterial microcompartment shells.

Bacterial microcompartments (BMCs) are polyhedral structures that segregate enzymatic cargo from the cytosol via encapsulation within a protein shell. Unlike other biological polyhedra, such as viral capsids and encapsulins, BMC shells can exhibit a highly advantageous structural and functional plasticity, conforming to a variety of anabolic (CO2 fixation in carboxysomes) and catabolic (nutrient assimilation in metabolosomes) roles. Consequently, understanding the subunit properties and associated protein-protein interaction processes that guide shell assembly and function is a necessary step to fully harness BMCs as modular, biotechnological nanomachines. Here, we describe the recent insights into the dynamics of structural features of the key BMC domain (Pfam00936)-containing proteins, which serve as a structural template for BMC-H and BMC-T shell building blocks.

Bacterial Proteins↗