Prediction of antibiotic resistance proteins from sequence-derived properties irrespective of sequence similarity

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Tetratricopeptide repeat domain protein 13 (TTC13) is a member of a large family of proteins known as tetratricopeptide repeat (TPR) proteins that has more than 5,000 members (Zeytuni 2012). One common feature of all TPR proteins is that they all contain TPR domains, which are thought to mediate protein-protein interactions and/or protein scaffolding. Interestingly, these TPR proteins are highly conserved between species. For example, sequence similarity between SUPPRESSOR of rps4 -RLD (SRFR1) and TTC13 was not only restricted to the TPR domain but also observed throughout the full length of both proteins. Extensive evidence suggested that SRFR1 was involved in pathogen resistance in plants by regulating resistance proteins in Arabidopsis thaliana (Kwon 2009). However, the mechanism by which SRFR1 regulated resistance proteins still remains unresolved. In contrast, nothing is known about the mammalian ortholog of SRFR1, TTC13. The goal of my project was to characterize TTC13 and to, ultimately, determine if TTC13 serves a similar role in mammals as SRFR1 in plants. Sequence analysis revealed that SRFR1 had 26% identity and 46% similarity at the amino acid level with TTC13. To begin addressing the role of TTC13 in mammals, I analyzed the expression of TTC13 mRNA and protein in mouse tissues. These analyses indicated that TTC13 mRNA was ubiquitously expressed in all examined mouse tissues. However, TTC13 protein expression varied in each tissue. For example, TTC13 protein was highly expressed in both kidney and liver, whereas TTC13 protein expression was not detectable in other tissues that were positive for TTC13 mRNA. Moreover, moderate protein expression was detected in the lung, heart and immune tissues (e.g. thymus, spleen, lymph nodes, T and B cells). To determine the cellular distribution of TTC13, I performed immunoflouresence and subcellular fractionation experiments. pFlag-TTC13 was localized to the cytoplasm in COS-1 cells by immunofluorescence. Cytoplasmic localization was confirmed by immunoblotting cytoplasmic and nuclear fractions for TTC13. Taken together, current evidence suggested that TTC13 was a cytoplasmic protein that was highly expressed in kidney and liver. Interestingly, TTC13 was also expressed in mammalian immune tissues in low to moderate levels, suggesting that TTC13 may have a role in the mammalian immune system. I conducted cell viability and cell cycle experiments in mammalian cell lines to investigate if TTC13 functions similarly to other TPR proteins.

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Prediction of Functional Class of Proteins and Peptides Irrespective of Sequence Homology by Support Vector Machines

Bioinformatics and Biology Insights ◽

10.4137/bbi.s315 ◽

2007 ◽

Vol 1 ◽

pp. BBI.S315 ◽

Cited By ~ 3

Author(s):

Zhi Qun Tang ◽

Hong Huang Lin ◽

Hai Lei Zhang ◽

Lian Yi Han ◽

Xin Chen ◽

...

Keyword(s):

Support Vector Machines ◽

Protein Function ◽

Wide Spectrum ◽

Sequence Similarity ◽

Functional Class ◽

Support Vector ◽

Homologous Proteins ◽

Vector Machines ◽

Derived Properties ◽

Proteins And Peptides

Various computational methods have been used for the prediction of protein and peptide function based on their sequences. A particular challenge is to derive functional properties from sequences that show low or no homology to proteins of known function. Recently, a machine learning method, support vector machines (SVM), have been explored for predicting functional class of proteins and peptides from amino acid sequence derived properties independent of sequence similarity, which have shown promising potential for a wide spectrum of protein and peptide classes including some of the low- and non-homologous proteins. This method can thus be explored as a potential tool to complement alignment-based, clustering-based, and structure-based methods for predicting protein function. This article reviews the strategies, current progresses, and underlying difficulties in using SVM for predicting the functional class of proteins. The relevant software and web-servers are described. The reported prediction performances in the application of these methods are also presented.

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Evaluation of a Structural Model ofPseudomonas aeruginosa Outer Membrane Protein OprM, an Efflux Component Involved in Intrinsic Antibiotic Resistance

Journal of Bacteriology ◽

10.1128/jb.183.1.367-374.2001 ◽

2001 ◽

Vol 183 (1) ◽

pp. 367-374 ◽

Cited By ~ 46

Author(s):

Kendy K. Y. Wong ◽

Fiona S. L. Brinkman ◽

Roland S. Benz ◽

Robert E. W. Hancock

Keyword(s):

Crystal Structure ◽

Antibiotic Resistance ◽

Membrane Protein ◽

Outer Membrane ◽

Outer Membrane Protein ◽

Structural Model ◽

Sequence Similarity ◽

Homologous Protein ◽

Related Family ◽

Resistance Nodulation Division

ABSTRACT The outer membrane protein OprM of Pseudomonas aeruginosa is involved in intrinsic and mutational multiple-antibiotic resistance as part of two resistance-nodulation-division efflux systems. The crystal structure of TolC, a homologous protein in Escherichia coli, was recently published (V. Koronakis, A. Sharff, E. Koronakis, B. Luisl, and C. Hughes, Nature 405:914–919, 2000), demonstrating a distinctive architecture comprising outer membrane β-barrel and periplasmic helical-barrel structures, which assemble differently from the common β-barrel-only conformation of porins. Based on their sequence similarity, a similar content of α-helical and β-sheet structure determined by circular dichroism spectroscopy, and our observation that OprM, like TolC, reconstitutes channels in planar bilayer membranes, OprM and TolC were considered to be structurally homologous, and a model of OprM was constructed by threading its sequence to the TolC crystal structure. Residues thought to be important for the TolC structure were conserved in space in this OprM model. Analyses of deletion mutants and previously isolated insertion mutants of OprM in the context of this model allowed us to propose roles for different protein domains. Our data indicate that the helical barrel of the protein is critical for both the function and the integrity of the protein, while a C-terminal domain localized around the equatorial plane of this helical barrel is dispensable. Extracellular loops appear to play a lesser role in substrate specificity for this efflux protein compared to classical porins, and there appears to be a correlation between the change in antimicrobial activity for OprM mutants and the pore size. Our model and channel formation studies support the “iris” mechanism of action for TolC and permit us now to form more focused hypotheses about the functional domains of OprM and its related family of efflux proteins.

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ZmaR, a Novel and Widespread Antibiotic Resistance Determinant That Acetylates Zwittermicin A

Journal of Bacteriology ◽

10.1128/jb.181.17.5455-5460.1999 ◽

1999 ◽

Vol 181 (17) ◽

pp. 5455-5460 ◽

Cited By ~ 12

Author(s):

Elizabeth A. Stohl ◽

Sean F. Brady ◽

Jon Clardy ◽

Jo Handelsman

Keyword(s):

Antibiotic Resistance ◽

Coenzyme A ◽

Sequence Similarity ◽

Covalent Modification ◽

Resistance Determinant ◽

Acetyl Coenzyme A ◽

Acetyl Coenzyme ◽

Cell Extracts ◽

Zwittermicin A

ABSTRACT ZmaR is a resistance determinant of unusual abundance in the environment and confers on gram-positive and gram-negative bacteria resistance to zwittermicin A, a novel broad-spectrum antibiotic produced by species of Bacillus. The ZmaR protein has no sequence similarity to proteins of known function; thus, the purpose of the present study was to determine the function of ZmaR in vitro. Cell extracts of E. coli containing zmaR inactivated zwittermicin A by covalent modification. Chemical analysis of inactivated zwittermicin A by 1H NMR, 13C NMR, and high- and low-resolution mass spectrometry demonstrated that the inactivated zwittermicin A was acetylated. Purified ZmaR protein inactivated zwittermicin A, and biochemical assays for acetyltransferase activity with [14C]acetyl coenzyme A demonstrated that ZmaR catalyzes the acetylation of zwittermicin A with acetyl coenzyme A as a donor group, suggesting that ZmaR may constitute a new class of acetyltransferases. Our results allow us to assign a biochemical function to a resistance protein that has no sequence similarity to proteins of known function, contributing fundamental knowledge to the fields of antibiotic resistance and protein function.

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Identification of antibiotic resistance proteins via MiCId's augmented workflow. A mass spectrometry-based proteomics approach

10.1101/2021.11.17.468978 ◽

2021 ◽

Author(s):

Gelio Alves ◽

Aleksey Y Ogurtsov ◽

Roger Karlsson ◽

Daniel Jaen-Luchoro ◽

Beatriz Pineiro-Iglesias ◽

...

Keyword(s):

Mass Spectrometry ◽

Antibiotic Resistance ◽

Pathogenic Bacteria ◽

High Sensitivity ◽

Multidrug Resistant ◽

Bacterial Strains ◽

Resistance Proteins ◽

Proteomics Approach ◽

Resistance Protein ◽

Microorganism Classification

Fast and accurate identifications of pathogenic bacteria along with their associated antibiotic resistance proteins are of paramount importance for patient treatments and public health. While mass spectrometry has become an important, technique for diagnostics of infectious disease, there is a need for mass spectrometry workflows offering this capability. To meet this need, we have augmented the previously published Microorganism Classification and Identification (MiCId) workflow for this capability. To evaluate the performance of the newly augmented MiCId workflow, we have used MS/MS datafiles from samples of 10 antibiotic resistance bacterial strains belonging to three different species: Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa. The evaluation results show that MiCId's workflow has a sensitivity value around 85% (with a lower bound at about 72%) and a precision greater than 95% in the identification of antibiotic resistance proteins. Using MS/MS datasets from samples of two bacterial clonal isolates, one being antibiotic-sensitive while the other (obtained from the same patient at different times) being multidrug-resistant, we applied MiCId's workflow to investigate possible mechanisms of antibiotic resistance in these pathogenic bacteria; the results showed that MiCId's conclusions are in agreement with the published study. Furthermore, we show that MiCId's workflow is fast. It provides microorganismal identifications, protein identifications, sample biomass estimates, and antibiotic resistance protein identifications in 6-17 minutes per MS/MS sample using computing resources that are available in most desktop and laptop computers, making it a highly portable workflow. This study demonstrated that MiCId's workflow is fast, portable, and with high sensitivity and high precision, making it a valuable tool for rapid identifications of bacteria as well as detection of their antibiotic resistance proteins. The new version of MiCId (v.07.01.2021) is freely available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

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Wide Variation in Antibiotic Resistance Proteins Identified by Functional Metagenomic Screening of a Soil DNA Library

Applied and Environmental Microbiology ◽

10.1128/aem.06759-11 ◽

2012 ◽

Vol 78 (6) ◽

pp. 1708-1714 ◽

Cited By ~ 36

Author(s):

Kelly M. McGarvey ◽

Konstantin Queitsch ◽

Stanley Fields

Keyword(s):

Antibiotic Resistance ◽

Protein Function ◽

Short Form ◽

Soil Dna ◽

Large Variability ◽

Content Type ◽

Resistance Proteins ◽

Dna Library ◽

Culture Independent ◽

Dihydrofolate Reductases

ABSTRACTMost genes for antibiotic resistance present in soil microbes remain unexplored because most environmental microbes cannot be cultured. Only recently has the identification of these genes become feasible through the use of culture-independent methods. We screened a soil metagenomic DNA library in anEscherichia colihost for genes that can confer resistance to kanamycin, gentamicin, rifampin, trimethoprim, chloramphenicol, or tetracycline. The screen revealed 41 genes that encode novel protein variants of eight protein families, including aminoglycoside acetyltransferases, rifampin ADP-ribosyltransferases, dihydrofolate reductases, and transporters. Several proteins of the same protein family deviate considerably from each other yet confer comparable resistance. For example, five dihydrofolate reductases sharing at most 44% amino acid sequence identity in pairwise comparisons were equivalent in conferring trimethoprim resistance. We identified variants of aminoglycoside acetyltransferases and transporters that differ in the specificity of the drugs for which they confer resistance. We also found wide variation in protein structure. Two forms of rifampin ADP-ribosyltransferases, one twice the size of the other, were similarly effective at conferring rifampin resistance, although the short form was expressed at a much lower level. Functional metagenomic screening provides insight into the large variability in antibiotic resistance protein sequences, revealing divergent variants that preserve protein function.

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Protocol for detection of bacterial proteins involved in efflux mediated antibiotic resistance (ARE) and their sub-families

10.21203/rs.3.pex-1371/v1 ◽

2021 ◽

Author(s):

Deeksha Pandey ◽

Bandana Kumari ◽

Neelja Singhal ◽

Manish Kumar

Keyword(s):

Antibiotic Resistance ◽

Prediction Method ◽

Query Protein ◽

Prediction Algorithm ◽

Support Vector ◽

Resistance Proteins ◽

Bacterial Proteins ◽

Proteomic Data ◽

Tier System ◽

Tier I

Abstract This protocol describes a method for detection of bacterial proteins involved in efflux mediated antibiotic resistance (ARE) and their sub-families as described in the research paper entitled "BacEffluxPred: A two-tier system to predict and categorize bacterial efflux mediated antibiotic resistance proteins” published in Scientific Reports. BacEffluxPred is a support vector machine based two-tier prediction method, that can be used for the detection of efflux proteins responsible for antibiotic resistance in bacteria and to identify the families to which it belongs. The overall prediction cycle includes three important steps: 1) The query protein is presented to the prediction algorithm. 2) If the query protein would be predicted to be a non-ARE protein, the prediction would stop at tier-I.3) If the query protein would be predicted as an ARE protein at the tier-I, the query protein would be forwarded to tier-II for ARE family prediction. By using these steps it is possible to generate the models that can be used on proteomic data to predict whether the given data have potential ARE proteins or not if yes it will further classified into their following families. This is the first in-silico tool for predicting bacterial ARE proteins and their families and it is freely available as both web-server and standalone versions at http://proteininformatics.org/mkumar/baceffluxpred/

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Recruitment of the mecA Gene Homologue ofStaphylococcus sciuri into a Resistance Determinant and Expression of the Resistant Phenotype inStaphylococcus aureus

Journal of Bacteriology ◽

10.1128/jb.183.8.2417-2424.2001 ◽

2001 ◽

Vol 183 (8) ◽

pp. 2417-2424 ◽

Cited By ~ 100

Author(s):

Shang Wei Wu ◽

Herminia de Lencastre ◽

Alexander Tomasz

Keyword(s):

Monoclonal Antibody ◽

Antibiotic Resistance ◽

Methicillin Resistance ◽

Sequence Similarity ◽

Meca Gene ◽

Plasmid Vector ◽

Resistance Determinant ◽

Susceptible Animal ◽

Methicillin Resistant ◽

Close Sequence

ABSTRACT Strains of methicillin-resistant Staphylococcus aureus (MRSA) have become the most important causative agents of hospital-acquired diseases worldwide. The genetic determinant of resistance, mecA, is not a gene native to S. aureus but was acquired from an extraspecies source by an unknown mechanism. We recently identified a close homologue of this gene in isolates of Staphylococcus sciuri, a taxonomically primitive staphylococcal species recovered most frequently from rodents and primitive mammals. In spite of the close sequence similarity between the mecA homologue ofS. sciuri and the antibiotic resistance determinantmecA of S. aureus, S. sciuri strains were found to be uniformly susceptible to β-lactam antibiotics. In an attempt to activate the apparently “silent” mecA gene of S. sciuri, a methicillin-resistant derivative, K1M200 (for which the MIC of methicillin is 200 μg/ml), was obtained through stepwise exposure of the parental strain S. sciuri K1 (methicillin MIC of 4 μg/ml) to increasing concentrations of methicillin. DNA sequencing of the mecA homologue from K1M200 revealed the introduction of a point mutation into the −10 consensus of the promoter: the replacement of a thymine residue at nucleotide 1577 in the susceptible strain K1 by adenine in the resistant strain K1M200, which was accompanied by a drastic increase in transcription rate and the appearance of a new protein that reacted with monoclonal antibody prepared against the penicillin-binding protein 2A (PBP2A), i.e., the gene product of S. aureus mecA. Transduction ofmecA from K1M200 (cloned into a plasmid vector) into a methicillin-susceptible S. aureus mutant resulted in a significant increase of methicillin resistance (from a methicillin MIC of 4 μg/ml to 12 and up to 50 μg/ml), the appearance of a low-affinity PBP detectable by the fluorographic assay, and the production of a protein that reacted in a Western blot with monoclonal antibody to PBP2A. Antibiotic resistance and the protein products disappeared upon removal of the plasmid-borne mecAhomologue. The observations support the proposition that themecA homologue ubiquitous in the antibiotic-susceptible animal species S. sciuri may be an evolutionary precursor of the methicillin resistance gene mecA of the pathogenic strains of MRSA.

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Characterization of the Pig Gut Microbiome and Antibiotic Resistome in Industrialized Feedlots in China

mSystems ◽

10.1128/msystems.00206-19 ◽

2019 ◽

Vol 4 (6) ◽

Cited By ~ 5

Author(s):

Chunlai Wang ◽

Peng Li ◽

Qiulong Yan ◽

Liping Chen ◽

Tiantian Li ◽

...

Keyword(s):

Antibiotic Resistance ◽

Resistance Genes ◽

Gut Microbiome ◽

Human Microbiome ◽

Antibiotic Resistance Genes ◽

Tetracycline Resistance ◽

Aminoglycoside Resistance ◽

Pig Production ◽

Resistance Proteins ◽

Gene Catalogue

ABSTRACT To characterize the diversity and richness and explore the function and structure of swine gut microbiome and resistome in common pig-farming feedlots, we sampled and metagenomic sequenced the feces of pigs from four different industrialized feedlots located in four distant provinces across China. Surprisingly, more than half of the nonredundant genes (1,937,648, 54.3%) in the current catalogue were newly found compared with the previously published reference gene catalogue (RGC) of the pig gut microbiome. Additionally, 16 high-completeness draft genomes were obtained by analyzing the dominant species on each feedlot. Notably, seven of these species often appeared in the human body sites. Despite a smaller number of nonredundant genes, our study identified more antibiotic resistance genes than those available in the RGC. Tetracycline, aminoglycoside, and multidrug resistance genes accounted for nearly 70% of the relative abundance in the current catalogue. Slightly higher sharing ratios were shown between the industrialized feedlot pig gut microbiomes and human gut microbiomes than that between the RGC and human counterpart (14.7% versus 12.6% in genes and 94.1% versus 87.7% in functional groups, respectively). Furthermore, a remarkably high number of the antibiotic resistance proteins (n =141) were identified to be shared by the pig, human, and mouse resistome, indicating the potential for horizontal transfer of resistance genes. Of the antibiotic resistance proteins shared by pigs and humans, 50 proteins were related to tetracycline resistance, and 49 were related to aminoglycoside resistance. IMPORTANCE The gut microbiota is believed to be closely related to many important physical functions in the host. Comprehensive data on mammalian gut metagenomes has facilitated research on host-microbiome interaction mechanisms, but less is known about pig gut microbiome, especially the gut microbiome in industrialized feedlot pigs, compared with human microbiome. On the other hand, pig production, as an important source of food, is believed to exacerbate the antibiotic resistance in humans due to the abuse of antibiotics in pig production in various parts of the world. This study delineates an intricate picture of swine gut microbiome and antibiotic resistome in industrialized feedlots and may provide insight for the pig producing industry.

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OXA-484, an OXA-48-Type Carbapenem-Hydrolyzing Class D β-Lactamase From Escherichia coli

Frontiers in Microbiology ◽

10.3389/fmicb.2021.660094 ◽

2021 ◽

Vol 12 ◽

Author(s):

Julian Sommer ◽

Kristina M. Gerbracht ◽

Felix F. Krause ◽

Florian Wild ◽

Manuela Tietgen ◽

...

Keyword(s):

Escherichia Coli ◽

Antibiotic Resistance ◽

North Africa ◽

Sequence Similarity ◽

Resistance Pattern ◽

High Sequence Similarity ◽

Low Frequencies ◽

Gram Negative ◽

E Coli ◽

Class D

OXA-48-like carbapenemases are among the most frequent carbapenemases in Gram-negative Enterobacterales worldwide with the highest prevalence in the Middle East, North Africa and Europe. Here, we investigated the so far uncharacterized carbapenemase OXA-484 from a clinical E. coli isolate belonging to the high-risk clone ST410 regarding antibiotic resistance pattern, horizontal gene transfer (HGT) and genetic support. OXA-484 differs by the amino acid substitution 214G compared to the most closely related variants OXA-181 (214R) and OXA-232 (214S). The blaOXA–484 was carried on a self-transmissible 51.5 kb IncX3 plasmid (pOXA-484) showing high sequence similarity with plasmids harboring blaOXA–181. Intraspecies and intergenus HGT of pOXA-484 to different recipients occurred at low frequencies of 1.4 × 10–7 to 2.1 × 10–6. OXA-484 increased MICs of temocillin and carbapenems similar to OXA-232 and OXA-244, but lower compared with OXA-48 and OXA-181. Hence, OXA-484 combines properties of OXA-181-like plasmid support and transferability as well as β-lactamase activity of OXA-232.

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