Structural basis of lipid binding for the membrane-embedded tetraacyldisaccharide-1-phosphate 4'-kinase LpxK

Machine learning for identifying resistance features of Klebsiella pneumoniae using whole-genome sequence single nucleotide polymorphisms

Introduction. Klebsiella pneumoniae, a gram-negative bacterium, is a common pathogen causing nosocomial infection. The drug-resistance rate of K. pneumoniae is increasing year by year, posing a severe threat to public health worldwide. K. pneumoniae has been listed as one of the pathogens causing the global crisis of antimicrobial resistance in nosocomial infections. We need to explore the drug resistance of K. pneumoniae for clinical diagnosis. Single nucleotide polymorphisms (SNPs) are of high density and have rich genetic information in whole-genome sequencing (WGS), which can affect the structure or expression of proteins. SNPs can be used to explore mutation sites associated with bacterial resistance.Hypothesis/Gap Statement. Machine learning methods can detect genetic features associated with the drug resistance of K. pneumoniae from whole-genome SNP data.Aims. This work used Fast Feature Selection (FFS) and Codon Mutation Detection (CMD) machine learning methods to detect genetic features related to drug resistance of K. pneumoniae from whole-genome SNP data.Methods. WGS data on resistance of K. pneumoniae strains to four antibiotics (tetracycline, gentamicin, imipenem, amikacin) were downloaded from the European Nucleotide Archive (ENA). Sequence alignments were performed with MUMmer 3 to complete SNP calling using K. pneumoniae HS11286 chromosome as the reference genome. The FFS algorithm was applied to feature selection of the SNP dataset. The training set was constructed based on mutation sites with mutation frequency >0.995. Based on the original SNP training set, 70% of SNPs were randomly selected from each dataset as the test set to verify the accuracy of the training results. Finally, the resistance genes were obtained by the CMD algorithm and Venny.Results. The number of strains resistant to tetracycline, gentamicin, imipenem and amikacin was 931, 1048, 789 and 203, respectively. Machine learning algorithms were applied to the SNP training set and test set, and 28 and 23 resistance genes were predicted, respectively. The 28 resistance genes in the training set included 22 genes in the test set, which verified the accuracy of gene prediction. Among them, some genes (KPHS_35310, KPHS_18220, KPHS_35880, etc.) corresponded to known resistance genes (Eef2, lpxK, MdtC, etc). Logistic regression classifiers were established based on the identified SNPs in the training set. The area under the curves (AUCs) of the four antibiotics was 0.939, 0.950, 0.912 and 0.935, showing a strong ability to predict bacterial resistance.Conclusion. Machine learning methods can effectively be used to predict resistance genes and associated SNPs. The FFS and CMD algorithms have wide applicability. They can be used for the drug-resistance analysis of any microorganism with genomic variation and phenotypic data. This work lays a foundation for resistance research in clinical applications.

Current Progress in the Structural and Biochemical Characterization of Proteins Involved in the Assembly of Lipopolysaccharide

The lipid component of the outer leaflet of the outer membrane of Gram-negative bacteria is primarily composed of the glycolipid lipopolysaccharide (LPS), which serves to form a protective barrier against hydrophobic toxins and many antibiotics. LPS is comprised of three regions: the lipid A membrane anchor, the nonrepeating core oligosaccharide, and the repeating O-antigen polysaccharide. The lipid A portion is also referred to as endotoxin as its overstimulation of the toll-like receptor 4 during systemic infection precipitates potentially fatal septic shock. Because of the importance of LPS for the viability and virulence of human pathogens, understanding how LPS is synthesized and transported to the outer leaflet of the outer membrane is important for developing novel antibiotics to combat resistant Gram-negative strains. The following review describes the current state of our understanding of the proteins responsible for the synthesis and transport of LPS with an emphasis on the contribution of protein structures to our understanding of their functions. Because the lipid A portion of LPS is relatively well conserved, a detailed description of the biosynthetic enzymes in the Raetz pathway of lipid A synthesis is provided. Conversely, less well-conserved biosynthetic enzymes later in LPS synthesis are described primarily to demonstrate conserved principles of LPS synthesis. Finally, the conserved LPS transport systems are described in detail.

A Metagenome-Wide Association Study and Arrayed Mutant Library Confirm Acetobacter Lipopolysaccharide Genes Are Necessary for Association with Drosophila melanogaster

A metagenome wide association (MGWA) study of bacterial host association determinants in Drosophila predicted that LPS biosynthesis genes are significantly associated with host colonization. We were unable to create site-directed mutants for each of the predicted genes in Acetobacter, so we created an arrayed transposon insertion library using Acetobacter fabarum DsW_054 isolated from Drosophila. Creation of the A. fabarum DsW_054 gene knock-out library was performed by combinatorial mapping and Illumina sequencing of random transposon insertion mutants. Transposon insertion locations for 6,418 mutants were successfully mapped, including hits within 63% of annotated genes in the A. fabarum DsW_054 genome. For 45/45 members of the library, insertion sites were verified by arbitrary PCR and Sanger sequencing. Mutants with insertions in four different LPS biosynthesis genes were selected from the library to validate the MGWA predictions. Insertion mutations in two genes biosynthetically upstream of Lipid-A formation, lpxC and lpxB, show significant differences in host association, whereas mutations in two genes encoding LPS biosynthesis functions downstream of Lipid-A biosynthesis had no effect. These results suggest an impact of bacterial cell surface molecules on the bacterial capacity for host association. Also, the transposon insertion mutant library will be a useful resource for ongoing research on the genetic basis for Acetobacter traits.

Crystal structure of lipid A disaccharide synthase LpxB from Escherichia coli

Most Gram-negative bacteria are surrounded by a glycolipid called lipopolysaccharide (LPS), which forms a barrier to hydrophobic toxins and, in pathogenic bacteria, is a virulence factor. During LPS biosynthesis, a membrane-associated glycosyltransferase (LpxB) forms a tetra-acylated disaccharide that is further acylated to form the membrane anchor moiety of LPS. Here we solve the structure of a soluble and catalytically competent LpxB by X-ray crystallography. The structure reveals that LpxB has a glycosyltransferase-B family fold but with a highly intertwined, C-terminally swapped dimer comprising four domains. We identify key catalytic residues with a product, UDP, bound in the active site, as well as clusters of hydrophobic residues that likely mediate productive membrane association or capture of lipidic substrates. These studies provide the basis for rational design of antibiotics targeting a crucial step in LPS biosynthesis.

Structure, inhibition, and regulation of essential lipid A enzymes

The Raetz pathway of lipid A biosynthesis plays a vital role in the survival and fitness of Gram-negative bacteria. Research efforts in the past three decades have identified individual enzymes of the pathway and have provided a mechanistic understanding of the action and regulation of these enzymes at the molecular level. This article reviews the discovery, biochemical and structural characterization, and regulation of the essential lipid A enzymes, as well as continued efforts to develop novel antibiotics against Gram-negative pathogens by targeting lipid A biosynthesis. This article is part of a Special Issue entitled: Bacterial Lipids edited by Russell E. Bishop.

Interfacial Enzymes: Membrane Binding, Orientation, Membrane Insertion, and Activity

Most interfacial enzymes undergo activation upon membrane binding. Interfacial activation is determined not only by the binding strength but also by the specific mode of protein-membrane interactions, including the angular orientation and membrane insertion of the enzymes. This chapter describes biophysical techniques to quantitatively evaluate membrane binding, orientation, membrane insertion, and activity of secreted phospholipase A2 (PLA2) and lipoxygenase (LO) enzymes. Procedures for recombinant production and purification of human pancreatic PLA2 and human 5-lipoxygenase (5-LO) are also presented. Several methods for measurements of membrane binding of peripheral proteins are described, i.e., fluorescence resonance energy transfer (FRET) from tryptophan or tyrosine residues of the protein to a fluorescent lipid in vesicles, changes in fluorescence of an environment-sensitive fluorescent lipid upon binding of proteins to membranes, and attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy. These methods produce the apparent binding constant, the protein-to-lipid binding stoichiometry, and the Hill cooperativity coefficient. Experimental procedures for segmental isotope labeling of proteins and determination of the orientation of membrane-bound proteins by polarized ATR-FTIR spectroscopy are described. Furthermore, evaluation of membrane insertion of peripheral proteins by a fluorescence quenching technique is outlined. Combination of the orientation and membrane insertion provides a unique configuration of the protein-membrane complex and hence elucidates certain details of the enzyme function, such as the modes of acquisition of a membrane-residing substrate and product release. Finally, assays for determination of the activities of secreted PLA2, soybean LO, and human 5-LO are described.

Sphingosine Kinases: Emerging Structure-Function Insights

Sphingosine kinases (SK1 and SK2) catalyse the conversion of sphingosine into sphingosine 1-phosphate and control fundamental cellular processes, including cell survival, proliferation, differentiation, migration, and immune function. In this review, we highlight recent breakthroughs in the structural and functional characterisation of SK1 and these are contextualised by analysis of crystal structures for closely related prokaryotic lipid kinases. We identify a putative dimerisation interface and propose novel regulatory mechanisms governing structural plasticity induced by phosphorylation and interaction with phospholipids and proteins. Our analysis suggests that the catalytic function and regulation of the enzymes might be dependent on conformational mobility and it provides a roadmap for future interrogation of SK1 function and its role in physiology and disease.