Oral Beta-Lactamase Protects the Canine Gut Microbiome from Oral Amoxicillin-Mediated Damage

Antibiotics damage the gut microbiome, which can result in overgrowth of pathogenic microorganisms and emergence of antibiotic resistance. Inactivation of antibiotics in the small intestine represents a novel strategy to protect the colonic microbiota. SYN-004 (ribaxamase) is a beta-lactamase formulated for oral delivery intended to degrade intravenously administered beta-lactam antibiotics in the gastrointestinal (GI) tract. The enteric coating of ribaxamase protects the enzyme from stomach acid and mediates pH-dependent release in the upper small intestine, the site of antibiotic biliary excretion. Clinical benefit was established in animal and human studies in which ribaxamase was shown to degrade ceftriaxone in the GI tract, thereby preserving the gut microbiome, significantly reducing Clostridioides difficile disease, and attenuating antibiotic resistance. To expand ribaxamase utility to oral beta-lactams, delayed release formulations of ribaxamase, SYN-007, were engineered to allow enzyme release in the lower small intestine, distal to the site of oral antibiotic absorption. Based on in vitro dissolution profiles, three SYN-007 formulations were selected for evaluation in a canine model of antibiotic-mediated gut dysbiosis. Dogs received amoxicillin (40 mg/kg, PO, TID) +/- SYN-007 (10 mg, PO, TID) for five days. Serum amoxicillin levels were measured after the first and last antibiotic doses and gut microbiomes were evaluated using whole genome shotgun sequence metagenomics analyses of fecal DNA prior to and after antibiotic treatment. Serum amoxicillin levels did not significantly differ +/- SYN-007 after the first dose for all SYN-007 formulations, while only one SYN-007 formulation did not significantly reduce systemic antibiotic concentrations after the last dose. Gut microbiomes of animals receiving amoxicillin alone displayed significant loss of diversity and emergence of antibiotic resistance genes. In contrast, for animals receiving amoxicillin + SYN-007, microbiome diversities were not altered significantly and the presence of antibiotic resistance genes was reduced. These data demonstrate that SYN-007 diminishes amoxicillin-mediated microbiome disruption and mitigates emergence and propagation of antibiotic resistance genes without interfering with antibiotic systemic absorption. Thus, SYN-007 has the potential to protect the gut microbiome by inactivation of beta-lactam antibiotics when administered by both oral and parenteral routes and to reduce emergence of antibiotic-resistant pathogens.

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Appearance of synthetic vector-associated antibiotic resistance genes in next-generation sequences

10.1101/392225 ◽

2018 ◽

Author(s):

George Taiaroa ◽

Gregory M. Cook ◽

Deborah A Williamson

Keyword(s):

Antibiotic Resistance ◽

Resistance Genes ◽

Sequence Data ◽

Antibiotic Resistance Genes ◽

Data Sets ◽

Next Generation ◽

Beta Lactam ◽

Sequence Contigs ◽

Beta Lactam Antibiotics ◽

Genome Shotgun Sequence

SynopsisBackgroundNext-generation sequencing methods have broad application in addressing increasing antibiotic resistance, with identification of antibiotic resistance genes (ARGs) having direct clinical relevance.ObjectivesHere, we describe the appearance of synthetic vector-associated ARGs in major public next-generation sequence data sets and assemblies, including in environmental samples and high priority pathogenic microorganisms.MethodsA search of selected databases – the National Centre for Biotechnology Information (NCBI) nucleotide collection, NCBI whole genome shotgun sequence contigs and literature-associated European Nucleotide Archive (ENA) datasets, was carried out using sequences characteristic of pUC-family synthetic vectors as a query in BLASTn. Identified hits were confirmed as being of synthetic origin, and further explored through alignment and comparison to primary read sets.ResultsSynthetic vectors are attributed to a range of organisms in each of the NCBI databases searched, including examples belonging to each Kingdom of life. These synthetic vectors are associated with various ARGs, primarily those encoding resistance to beta-lactam antibiotics and aminoglycosides. Synthetic vector associated ARGs are also observed in multiple environmental meta-transcriptome datasets, as shown through analysis of associated ENA primary reads, and are proposed to have led to incorrect statements being made in the literature on the abundance of ARGs.ConclusionsAppearance of synthetic vector-associated ARGs can confound the study of antimicrobial resistance in varied settings, and may have clinical implications in the nearfuture.

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An Orally Delivered Beta-Lactamase Protects the Gut Microbiome from Antibiotic-Mediated Damage and Mitigates the Propagation of Antibiotic-Resistance Genes in a Porcine Dysbiosis Model

Gastroenterology ◽

10.1016/s0016-5085(17)34350-0 ◽

2017 ◽

Vol 152 (5) ◽

pp. S1305-S1306

Author(s):

Sheila Connelly ◽

Christian Furlan Freguia ◽

Poorani Subramanian ◽

Nur A. Hasan ◽

Rita R. Colwell ◽

...

Keyword(s):

Antibiotic Resistance ◽

Resistance Genes ◽

Gut Microbiome ◽

Antibiotic Resistance Genes ◽

Beta Lactamase

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Identification, Characterization, and Formulation of a Novel Carbapenemase Intended to Prevent Antibiotic-Mediated Gut Dysbiosis

Microorganisms ◽

10.3390/microorganisms7010022 ◽

2019 ◽

Vol 7 (1) ◽

pp. 22 ◽

Cited By ~ 1

Author(s):

Sheila Connelly ◽

Todd Parsley ◽

Hui Ge ◽

Michael Kaleko

Keyword(s):

Gut Microbiome ◽

Opportunistic Infections ◽

New Delhi ◽

Beta Lactamase ◽

Gi Tract ◽

Beta Lactam ◽

Klebsiella Pneumoniae Carbapenemase ◽

Beta Lactam Antibiotics ◽

Antibiotic Degradation

Antibiotics can damage the gut microbiome leading to opportunistic infections and the emergence of antibiotic resistance. Microbiome protection via antibiotic inactivation in the gastrointestinal (GI) tract represents a strategy to limit antibiotic exposure of the colonic microbiota. Proof of concept for this approach was achieved with an orally-administered beta-lactamase enzyme, SYN-004 (ribaxamase), that was demonstrated to degrade ceftriaxone excreted into the GI tract and protect the gut microbiome from antibiotic-mediated dysbiosis. Ribaxamase efficiently degrades penicillin and cephalosporin beta-lactam antibiotics, but is not active against carbapenems. To expand this microbiome protection strategy to include all classes of beta-lactams, three distinct carbapenemases were evaluated for manufacturability, antibiotic degradation spectrum, and stability in human intestinal fluid. E. coli production strains were generated for P2A, a novel metallo-enzyme isolated from B. cereus, New Delhi metallo-beta-lactamase (NDM), and Klebsiella pneumoniae carbapenemase (KPC). While all three enzymes effectively inactivated a broad range of antibiotics, including penicillins, most cephalosporins, and carbapenems in vitro, only P2A retained biological activity when incubated with human chyme. As functional stability in the intestinal tract is a key requirement for an orally-delivered enzyme, P2A was chosen as a potential clinical candidate. An enteric formulation of P2A was developed, called SYN-006, that was inert under high acid conditions, with enzyme dissolution occurring at pH > 5.5. SYN-006 has the potential to expand microbiome protection via antibiotic inactivation to include all classes of beta-lactam antibiotics.

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Machine learning leveraging genomes from metagenomes identifies influential antibiotic resistance genes in the infant gut microbiome

10.1101/185348 ◽

2017 ◽

Cited By ~ 1

Author(s):

Sumayah F. Rahman ◽

Matthew R. Olm ◽

Michael J. Morowitz ◽

Jillian F. Banfield

Keyword(s):

Machine Learning ◽

Antibiotic Resistance ◽

Relative Abundance ◽

Resistance Genes ◽

Gut Microbiome ◽

Statistical Tests ◽

Antibiotic Resistance Genes ◽

Major Facilitator Superfamily ◽

Antibiotic Administration ◽

Beta Lactamase

AbstractAntibiotic resistance in pathogens is extensively studied, yet little is known about how antibiotic resistance genes of typical gut bacteria influence microbiome dynamics. Here, we leverage genomes from metagenomes to investigate how genes of the premature infant gut resistome correspond to the ability of bacteria to survive under certain environmental and clinical conditions. We find that formula feeding impacts the resistome. Random forest models corroborated by statistical tests revealed that the gut resistome of formula-fed infants is enriched in class D beta-lactamase genes. Interestingly,Clostridium difficilestrains harboring this gene are at higher abundance in formula-fed infants compared toC. difficilelacking this gene. Organisms with genes for major facilitator superfamily drug efflux pumps have faster replication rates under all conditions, even in the absence of antibiotic therapy. Using a machine learning approach, we identified genes that are predictive of an organism’s direction of change in relative abundance after administration of vancomycin and cephalosporin antibiotics. The most accurate results were obtained by reducing annotated genomic data into five principal components classified by boosted decision trees. Among the genes involved in predicting if an organism increased in relative abundance after treatment are those that encode for subclass B2 beta-lactamases and transcriptional regulators of vancomycin resistance. This demonstrates that machine learning applied to genome-resolved metagenomics data can identify key genes for survival after antibiotics and predict how organisms in the gut microbiome will respond to antibiotic administration.ImportanceThe process of reconstructing genomes from environmental sequence data (genome-resolved metagenomics) allows for unique insight into microbial systems. We apply this technique to investigate how the antibiotic resistance genes of bacteria affect their ability to flourish in the gut under various conditions. Our analysis reveals that strain-level selection in formula-fed infants drives enrichment of beta-lactamase genes in the gut resistome. Using genomes from metagenomes, we built a machine learning model to predict how organisms in the gut microbial community respond to perturbation by antibiotics. This may eventually have clinical and industrial applications.

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SYN-007, an Orally Administered Beta-Lactamase Enzyme, Protects the Gut Microbiome from Oral Amoxicillin/Clavulanate without Adversely Affecting Antibiotic Systemic Absorption in Dogs

Microorganisms ◽

10.3390/microorganisms8020152 ◽

2020 ◽

Vol 8 (2) ◽

pp. 152 ◽

Cited By ~ 2

Author(s):

Sheila Connelly ◽

Brian Fanelli ◽

Nur A. Hasan ◽

Rita R. Colwell ◽

Michael Kaleko

Keyword(s):

Antibiotic Resistance ◽

Gastrointestinal Tract ◽

Gut Microbiome ◽

Antibiotic Resistance Genes ◽

Systemic Absorption ◽

Beta Lactamase ◽

Beta Lactam ◽

Oral Amoxicillin ◽

Amoxicillin Clavulanate ◽

Lactamase Inhibitor

Beta-lactamases, enzymes produced by bacteria to degrade beta-lactam antibiotics, have been harnessed as therapeutics to protect the gut microbiome from damage caused by antibiotics. Proof-of-concept of this approach using SYN-004 (ribaxamase), a beta-lactamase formulated for oral delivery with intravenous (IV) penicillins and cephalosporins, was demonstrated with animal models and in humans. Ribaxamase degraded ceftriaxone in the gastrointestinal tract, protected the gut microbiome, significantly reduced the incidence of Clostridioides difficile disease and attenuated emergence of antibiotic resistant organisms. SYN-007 is a delayed release formulation of ribaxamase intended for use with oral beta-lactams. In dogs treated with oral amoxicillin, SYN-007 diminished antibiotic-mediated microbiome disruption and reduced the emergence of antibiotic resistance without altering amoxicillin systemic absorption. Here, SYN-007 function in the presence of clavulanate, a beta-lactamase inhibitor, was investigated. Dogs received amoxicillin (40 mg/kg, orally (PO), three times a day (TID)) or the combined antibiotic/beta-lactamase inhibitor, amoxicillin/clavulanate (40 mg/kg amoxicillin, 5.7 mg/kg clavulanate, PO, TID) +/™ SYN-007 (10 mg, PO, TID) for five days. Serum amoxicillin levels were not significantly different +/™ SYN-007 compared to amoxicillin alone or amoxicillin/clavulanate alone as controls for both first and last doses, indicating SYN-007 did not interfere with systemic absorption of the antibiotic. Whole genome shotgun metagenomics analyses of the fecal microbiomes demonstrated both amoxicillin and amoxicillin/clavulanate significantly reduced diversity and increased the frequency of antibiotic resistance genes. Microbiome damage appeared more severe with amoxicillin/clavulanate. In contrast, with SYN-007, microbiome diversity was not significantly altered, and frequency of antibiotic resistance genes did not increase. Importantly, SYN-007 functioned in the presence of clavulanate to protect the gut microbiome indicating that SYN-007 activity was not inhibited by clavulanate in the dog gastrointestinal tract. SYN-007 has the potential to expand microbiome protection to beta-lactam/beta-lactamase inhibitor combinations delivered orally or systemically.

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HMD-ARG: hierarchical multi-task deep learning for annotating antibiotic resistance genes

Microbiome ◽

10.1186/s40168-021-01002-3 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Yu Li ◽

Zeling Xu ◽

Wenkai Han ◽

Huiluo Cao ◽

Ramzan Umarov ◽

...

Keyword(s):

Antibiotic Resistance ◽

Deep Learning ◽

Resistance Genes ◽

Antibiotic Resistance Genes ◽

Third Party ◽

Superior Performance ◽

Beta Lactamase ◽

Learning Framework ◽

Sequence Encoding ◽

Global Threat

Abstract Background The spread of antibiotic resistance has become one of the most urgent threats to global health, which is estimated to cause 700,000 deaths each year globally. Its surrogates, antibiotic resistance genes (ARGs), are highly transmittable between food, water, animal, and human to mitigate the efficacy of antibiotics. Accurately identifying ARGs is thus an indispensable step to understanding the ecology, and transmission of ARGs between environmental and human-associated reservoirs. Unfortunately, the previous computational methods for identifying ARGs are mostly based on sequence alignment, which cannot identify novel ARGs, and their applications are limited by currently incomplete knowledge about ARGs. Results Here, we propose an end-to-end Hierarchical Multi-task Deep learning framework for ARG annotation (HMD-ARG). Taking raw sequence encoding as input, HMD-ARG can identify, without querying against existing sequence databases, multiple ARG properties simultaneously, including if the input protein sequence is an ARG, and if so, what antibiotic family it is resistant to, what resistant mechanism the ARG takes, and if the ARG is an intrinsic one or acquired one. In addition, if the predicted antibiotic family is beta-lactamase, HMD-ARG further predicts the subclass of beta-lactamase that the ARG is resistant to. Comprehensive experiments, including cross-fold validation, third-party dataset validation in human gut microbiota, wet-experimental functional validation, and structural investigation of predicted conserved sites, demonstrate not only the superior performance of our method over the state-of-art methods, but also the effectiveness and robustness of the proposed method. Conclusions We propose a hierarchical multi-task method, HMD-ARG, which is based on deep learning and can provide detailed annotations of ARGs from three important aspects: resistant antibiotic class, resistant mechanism, and gene mobility. We believe that HMD-ARG can serve as a powerful tool to identify antibiotic resistance genes and, therefore mitigate their global threat. Our method and the constructed database are available at http://www.cbrc.kaust.edu.sa/HMDARG/.

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Novel Soil-Derived Beta-Lactam, Chloramphenicol, Fosfomycin and Trimethoprim Resistance Genes Revealed by Functional Metagenomics

Antibiotics ◽

10.3390/antibiotics10040378 ◽

2021 ◽

Vol 10 (4) ◽

pp. 378

Author(s):

Inka Marie Willms ◽

Maja Grote ◽

Melissa Kocatürk ◽

Lukas Singhoff ◽

Alina Andrea Kraft ◽

...

Keyword(s):

Antibiotic Resistance ◽

Resistance Genes ◽

Antibiotic Resistance Genes ◽

Reference Database ◽

Functional Metagenomics ◽

Beta Lactam ◽

Public Attention ◽

Soil Ecosystems ◽

High Level ◽

Antibiotic Efflux

Antibiotic resistance genes (ARGs) in soil are considered to represent one of the largest environmental resistomes on our planet. As these genes can potentially be disseminated among microorganisms via horizontal gene transfer (HGT) and in some cases are acquired by clinical pathogens, knowledge about their diversity, mobility and encoded resistance spectra gained increasing public attention. This knowledge offers opportunities with respect to improved risk prediction and development of strategies to tackle antibiotic resistance, and might help to direct the design of novel antibiotics, before further resistances reach hospital settings or the animal sector. Here, metagenomic libraries, which comprise genes of cultivated microorganisms, but, importantly, also those carried by the uncultured microbial majority, were screened for novel ARGs from forest and grassland soils. We detected three new beta-lactam, a so far unknown chloramphenicol, a novel fosfomycin, as well as three previously undiscovered trimethoprim resistance genes. These ARGs were derived from phylogenetically diverse soil bacteria and predicted to encode antibiotic inactivation, antibiotic efflux, or alternative variants of target enzymes. Moreover, deduced gene products show a minimum identity of ~21% to reference database entries and confer high-level resistance. This highlights the vast potential of functional metagenomics for the discovery of novel ARGs from soil ecosystems.

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Growing Menace of Antibacterial Resistance in Clinical Isolates ofPseudomonas aeruginosain Nepal: An Insight of Beta-Lactamase Production

BioMed Research International ◽

10.1155/2016/6437208 ◽

2016 ◽

Vol 2016 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

Shamshul Ansari ◽

Rabindra Dhital ◽

Sony Shrestha ◽

Sangita Thapa ◽

Ram Puri ◽

...

Keyword(s):

Pseudomonas Aeruginosa ◽

Antibiotic Resistance ◽

Opportunistic Pathogen ◽

Resistance Rate ◽

Diffusion Method ◽

Beta Lactamase ◽

Beta Lactam ◽

Beta Lactam Antibiotics ◽

Microbiological Methods ◽

Immunosuppressed Patients

Introduction. Pseudomonas aeruginosais the most frequently isolated organism as it acts as the opportunistic pathogen and can cause infections in immunosuppressed patients. The production of different types of beta-lactamases renders this organism resistant to many commonly used antimicrobials. Therefore, the aim of this study was to document the antibiotic resistance rate inPseudomonas aeruginosaisolated from different clinical specimens.Methods. Pseudomonas aeruginosarecovered was identified by standard microbiological methods. Antibiotic susceptibility testing was performed by modified Kirby-Bauer disc diffusion method following Clinical and Laboratory Standard Institute (CLSI) guidelines and all the suspected isolates were tested for the production of ESBLs, MBLs, and AmpC.Results.Out of total (178) isolates, 83.1% were recovered from the inpatient department (IPD). Majority of the isolates mediated resistance towards the beta-lactam antibiotics, while nearly half of the isolates were resistant to ciprofloxacin. Most of the aminoglycosides used showed resistance rate up to 75% but amikacin proved to be better option. No resistance to polymyxin was observed. ESBLs, MBLs, and AmpC mediated resistance was seen in 33.1%, 30.9%, and 15.7% isolates, respectively.Conclusions. Antibiotic resistance rate and beta-lactamase mediated resistance were high. Thus, regular surveillance of drug resistance is of utmost importance.

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Monitoring and Evaluation of Antibiotic Resistance Genes in Three Rivers in Northeast China

10.21203/rs.3.rs-313046/v2 ◽

2021 ◽

Author(s):

Chen Zhao ◽

Chenyu Li ◽

Xiaoming Wang ◽

Zhuosong Cao ◽

Chao Gao ◽

...

Keyword(s):

Antibiotic Resistance ◽

River Water ◽

Resistance Genes ◽

Northeast China ◽

Pathogenic Bacteria ◽

Respiratory Infections ◽

Antibiotic Resistance Genes ◽

Distribution Characteristics ◽

Beta Lactam ◽

Three Rivers

Abstract Background: Antibiotic resistance genes (ARGs) have become an important public health problem. In this study, we used metagenomic sequencing to analyze the composition of ARGs in certain original habitats of northeast China, comprising three different rivers and riverbank soils of the Heilongjiang River, Tumen River, and Yalu River. Results: Twenty types of ARG were detected in every water sample. The major ARGs were multidrug resistance genes, at approximately 0.5 copies/16s rRNA, accounting for 57.5% of the total ARG abundance. The abundance of multidrug, bacitracin, beta-lactam, macrolide‑lincosamide‑streptogramin, sulfonamide, fosmidomycin, and polymyxin resistance genes covered 96.9% of the total ARG abundance. No significant ecological boundary of ARG diversity was observed. The compositions of the resistance genes in the three rivers were very similar to each other, and 92.1% of ARG subtypes were shared by all water samples. Except for vancomycin resistance genes, almost all ARGs in riverbank soils were detected in the river water. About 31.05% ARGs were carried by Pseudomonas. Opportunistic pathogenic bacteria carrying resistance genes were mainly related to diarrhea and respiratory infections. Multidrug and beta-lactam resistance genes correlated positively with mobile genetic elements (MGEs), indicating a potential risk of diffusion.Conclusions: The composition of ARGs in three different rivers was similar, indicating that climate played an important role in ARG occurrence. ARG subtypes in river water were almost completely the same as those in riverbank soil. ARGs had no significant geographical distribution characteristics. Many ARGs were carried by human pathogenic bacteria related to human diarrhea and respiratory infections, such as Pseudomonas aeruginosa and Aeromonas caviae. In general, our results provide a valuable dataset of river water ARG distribution in northeast China. The related ecological geography distribution characteristics should be further explored.

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