Biology subjects

Stelling, J.

Publications and source records attributed to Stelling, J..

At least 19 recordsLinked to original sources

bioRxiv2024

Scalable enumeration and sampling of minimal metabolic pathways for organisms and communities

Many interactions in microbial consortia or tissues of multicellular organisms rely on networks of metabolite exchanges. To predict community function and composition beyond statistical correlations, one can use genome-scale metabolic models. However, comprehensive model analysis via metabolic pathways is a major challenge because pathway counts grow combinatorially with model size. Here, we define minimal pathways that yield compact representations of metabolic network capabilities. They generalize existing pathway concepts by allowing inhomogeneous constraints and targeted analysis of subnetworks, and we show how to enumerate and sample them efficiently via iterative minimization and pathway graphs. This enables applications such as assessing quantitative gene essentiality in the central metabolism of Escherichia coli, predicting metabolite exchanges associated with homeostasis and health in a host-microbe model of the human gut, and designing butyrate-producing microbial communities. Minimal pathways enable scalable analysis of metabolic subnetworks such as metabolite exchanges in uni- and multicellular systems.

systems biology↗

bioRxiv2024

Evolverator: An engineered in cellulo yeast system to drive rapid continuous evolution of proteins

Continuous in vivo evolution of non-essential proteins requires an engineered link between target protein and host cell fitness, which is difficult to establish and vulnerable to escape mutations. We systematically designed and tested Saccharomyces cerevisiae gene circuits guided by quantitative mathematical models that predicted circuit, organism, and population behavior. We identified four generalizable design principles for escape-resistant continuous evolution and built the Evolverator, a yeast platform that couples protein binding to proliferation rate while suppressing escape mutations. We used the Evolverator to improve human estrogen receptor ligand affinity and generate stronger yeast repressors from the bacterial LacI protein. The resulting variants revealed previously undescribed hER substitutions within and outside the binding pocket, as well as LacI mutations that enhance repression in yeast despite reduced activity in Escherichia coli. Our work establishes a generalizable, model-guided framework for building yeast strains to allow continuous evolution of diverse protein functions in vivo.

synthetic biology↗

bioRxiv2023

ENKIE: A package for predicting enzyme kinetic parameter values and their uncertainties

Relating metabolite and enzyme abundances to metabolic fluxes requires reaction kinetics, core elements of dynamic and enzyme cost models. However, kinetic parameters have been measured only for a fraction of all known enzymes, and the reliability of the available values is unknown. The ENzyme KInetics Estimator (ENKIE) uses Bayesian Multilevel Models to predict value and uncertainty of KM and kcat parameters. Our models use five categorical predictors and achieve prediction performances comparable to deep learning approaches that use sequence and structure information. They provide accurate uncertainty predictions and interpretable insights into the main sources of uncertainty. We expect our tool to simplify the construction of priors for Bayesian kinetic models of metabolism.

systems biology↗

bioRxiv2022

Synthetic genotype networks

Genotype networks are sets of genotypes connected by small mutational changes that share the same phenotype. They facilitate evolutionary innovation by enabling the exploration of different neighborhoods in genotype space. Genotype networks, first suggested by theoretical models, have been empirically confirmed for proteins and RNAs. Comparative studies also support their existence for gene regulatory networks (GRNs), but direct experimental evidence is lacking. Here, we report the construction of three interconnected genotype networks of synthetic GRNs producing three distinct gene expression phenotypes in Escherichia coli. These genotype networks, composed of over twenty different synthetic GRNs, provide robustness in face of mutations while enabling transitions to innovative phenotypes. Through realistic mathematical modeling, we quantify robustness and evolvability for the complete genotype-phenotype map and link these features mechanistically to GRN motifs. Our work thereby exemplifies how GRN evolution along genotype networks might be driving evolutionary innovation.

synthetic biology↗

bioRxiv2022

Nucleobase adduct-containing metabolites are MR1 ligands that stimulate self-reactive MR1T cells

MR1T lymphocytes are a recently identified population of T cells that recognize unknown self-antigens presented by the non-polymorphic MHC-I-related molecule, MR1. MR1T cells can kill tumor cells and modulate the functions of other immune cells with promising therapeutic applications. By integrating genetic, pharmacological and biochemical approaches we identified carbonyl stress and alterations of nucleobase metabolism in tumor target cells that promote recognition by MR1 T cells. We dissected these pathways and found that nucleobase adduct-containing metabolites are self-antigens stimulating MR1T cells. Several nucleobase adducts are presented by MR1 molecules and stimulate individual MR1T cells. Our data suggest that MR1T cells are surveyor of cellular metabolic alterations occurring in conditions of metabolic stress, such as cancer, and lay the groundwork for the development of novel HLA-unrestricted T cell-based therapies.

immunology↗

bioRxiv2022

Cellular and computational models reveal environmental and genetic interactions in MMUT-type methylmalonic aciduria

MMUT-type methylmalonic aciduria is a rare inherited metabolic disease caused by the loss of function of the methylmalonyl-CoA mutase (MMUT) enzyme. Patients develop symptoms resembling those of primary mitochondrial disorders, but the underlying causes of mitochondrial dysfunction remain unclear. Here, we examined environmental and genetic interactions in MMUT deficiency using a combination of computational modeling and cellular models to decipher pathways interacting with MMUT. Immortalized fibroblast (hTERT BJ5ta) MMUT-KO (MUTKO) clones displayed a mild mitochondrial impairment in standard glucose-based medium, but they did not to show increased reliance on respiratory metabolism nor reduced growth or viability. Consistently, our modeling predicted MUTKO specific growth phenotypes only for lower extracellular glutamine concentrations. Indeed, two of three MMUT-deficient BJ5ta cell lines showed a reduced viability in glutamine-free medium. Further, growth on 183 different carbon and nitrogen substrates identified increased NADH (nicotinamide adenine dinucleotide) metabolism of BJ5ta and HEK293 MUTKO cells compared to controls on purine- and glutamine-based substrates. With this knowledge, our modeling predicted 13 reactions interacting with MMUT that potentiate an effect on growth, primarily those of secondary oxidation of propionyl-CoA, oxidative phosphorylation and oxygen diffusion. Of these, we validated 3-hydroxyisobutytyl-CoA hydrolase (HIBCH) in the secondary propionyl-CoA oxidation pathway. Altogether, these results suggest compensation for the loss of MMUT function by increasing anaplerosis through glutamine or by diverting flux away from MMUT through the secondary propionyl-CoA oxidation pathway, which may have therapeutic relevance. 1 sentence take-home messageBy perturbing metabolic pathways through genetic and environmental interventions in cellular and computational models of MMUT-type methylmalonic aciduria, we identified glutamine and secondary oxidative propionyl-CoA oxidation pathways as being important in the disease.

systems biology↗

bioRxiv2022

Genomic Surveillance of Salmonella spp. in the Philippines, 2013-2014

Increasing antimicrobial resistance (AMR) in Salmonella has been observed in the Philippines. This study aims to utilize whole genome sequencing (WGS) to characterize the population and AMR mechanisms of Salmonella captured by the Philippine Antimicrobial Resistance Surveillance Program (ARSP) and contrast to traditional laboratory methods. We sequenced the whole genomes of 148 Salmonella Typhi (S. Typhi) and 65 non-typhoidal Salmonella (NTS) collected in the Philippines in 2013-2014. From the genome sequences, we determined the serotype, multilocus sequence type, presence of determinants of antimicrobial resistance and relatedness between isolates. We also compared the genotypic predictions of serotype and AMR to the phenotypic data. AMR rates in S. Typhi were low, with sparse acquisition of mutations associated with reduced susceptibility to fluoroquinolones or extended-spectrum beta-lactamases (ESBL) genes. In contrast, three quarters of NTS isolates were insusceptible to at least one antimicrobial, with more than half carrying mutations and/or genes linked to resistance to fluoroquinolones. ESBL genes were detected in five genomes that also carried other AMR determinants. The population of S. Typhi was dominated by the likely endemic genotype 3.0, which also caused of a putative local outbreak susceptible to antibiotics. The main NTS clades were global epidemic S. Enteritidis ST11 and the monophasic variant of S. Typhimurium (I 4,[5],12:i:-) ST34, which had frequently been serotyped as S. Typhimurium in the laboratory. This was the first time that Salmonella isolated from the Philippines were characterized by WGS and we provide evidence of its utility for ongoing surveillance at the ARSP.

genomics↗

bioRxiv2021

Cell region fingerprints enable highly precise single-cell tracking and lineage reconstruction

Experimental studies of cell growth, inheritance, and their associated processes by microscopy require accurate single-cell observations of sufficient duration to reconstruct the genealogy. However, cell tracking--assigning identical cells on consecutive images to a track--is often challenging due to imperfect segmentation, moving cells, or focus drift, resulting in laborious manual verification. Here, we propose fingerprints to identify problematic assignments rapidly. A fingerprint distance measures the similarity between cells in two consecutive images by comparing the structural information contained in the low frequencies of a Fourier transform. We show that it is broadly applicable across cell types and image modalities, provided the image has sufficient structural information. Our tracker (TracX) uses the concept to reject unlikely assignments, thereby substantially increasing tracking performance on published and newly generated long-term data sets from various species. For S. cerevisiae, we propose a comprehensive model for cell size control at the single-cell and population level centered on the Whi5 regulator. It demonstrates how highly precise tracking can help uncover previously undescribed single-cell biology.

systems biology↗

bioRxiv2021

High interaction valency ensures cohesion and persistence of a microtubule +TIP body at the plus-end of a single specialized microtubule in yeast

Microtubule plus-end tracking proteins (+TIPs) control microtubule specialization and are as such essential notably during eukaryotic cell division. Here, we investigated interactions and functions of the budding yeast Kar9 network consisting of the core +TIPs components Kar9 (functional homologue of APC, MACF, and SLAIN), Bim1 (orthologue of EB1), and Bik1 (orthologue of CLIP-170). Our data indicate that a redundant, multivalent web of interactions links the three +TIPs together to form a "Kar9 body" at the tip of a single cytoplasmic microtubule. They further suggest that this body is a liquid-like condensate, allowing it to persist on both growing and shrinking microtubule tips, and functions as a mechanical coupling device between microtubules and actin cables during mitosis. Our study underlines the power of dissecting the web of low-affinity interactions driving liquid-liquid phase separation of proteins in order to demonstrate the importance and establish the functional roles of condensation processes in vivo.

cell biology↗

bioRxiv2021

Genome Sequencing Identifies Previously Unrecognized Klebsiella pneumoniae Outbreaks in Neonatal Intensive Care Units in the Philippines

BackgroundKlebsiella pneumoniae is a critically important pathogen in the Philippines. Isolates are commonly resistant to at least two classes of antibiotics, yet mechanisms and spread of its resistance are not well studied. MethodsA retrospective sequencing survey was performed on carbapenem-, extended spectrum beta-lactam- and cephalosporin-resistant Klebsiella pneumoniae isolated at 20 antimicrobial resistance (AMR) surveillance sentinel sites from 2015-2017. We characterized 259 isolates using biochemical methods, antimicrobial susceptibility testing, and whole genome sequencing (WGS). Known AMR mechanisms were identified. Potential outbreaks were investigated by detecting clusters from epidemiologic, phenotypic and genome-derived data. ResultsPrevalent AMR mechanisms detected include blaCTX-M-15 (76.8%) and blaNDM-1 (37.5%). An epidemic IncFII(Yp) plasmid carrying blaNDM-1 was also detected in 46 isolates from 6 sentinel sites and 14 different sequence types (ST). This plasmid was also identified as the main vehicle of carbapenem resistance in 2 previously unrecognized local outbreaks of ST348 and ST283 at 2 different sentinel sites. A third local outbreak of ST397 was also identified but without the IncFII(Yp) plasmid. Isolates in each outbreak site showed identical STs, K- and O-loci, and similar resistance profiles and AMR genes. All outbreak isolates were collected from blood of children aged <1. ConclusionWGS provided an in-depth understanding of the epidemiology of AMR in the Philippines, which was not possible with only phenotypic and epidemiologic data. The identification of three previously unrecognized Klebsiella outbreaks highlights the utility of WGS in outbreak detection, as well as its importance in public health and in implementing infection control programs. summaryWhole genome sequencing identified three distinct previously unrecognized local outbreaks in a retrospective study in the Philippines, along with an epidemic plasmid carrying antimicrobial resistance genes, highlighting its importance in antimicrobial resistance surveillance, outbreak detection and infection control.

genomics↗

bioRxiv2021

Genomic Surveillance of Acinetobacter baumannii in the Philippines, 2013-2014

Acinetobacter baumannii is an opportunistic nosocomial pathogen that has increasingly become resistant to carbapenems worldwide. In the Philippines, carbapenem resistance and multi-drug resistance (MDR) rates are above 50%. We undertook a genomic study of carbapenem resistant A. baumannii in the Philippines to characterize the population diversity and antimicrobial resistance (AMR) mechanisms. We sequenced the whole genomes of 117 A. baumannii isolates recovered by 16 hospitals in the Philippines between 2013 and 2014. We determined the multi-locus sequence type (MLST), presence of acquired AMR determinants and relatedness between isolates from the genome sequences. We also compared the phenotypic and genotypic resistance results. Carbapenem resistance was mainly explained by the acquisition of class-D beta-lactamase gene blaOXA-23. The concordance between phenotypic and genotypic resistance to imipenem was 98.15% and 94.97% overall for the seven antibiotics analysed. Twenty-two different sequence types (ST) were identified, including 7 novel STs. The population was dominated by high-risk international clone 2 (i.e., clonal complex 92), in particular by ST195 and ST208 and their single locus variants. With WGS we identified local clusters representing potential undetected nosocomial outbreaks, as well as multi-hospital clusters indicating inter-hospital transmission. Comparison with global genomes suggested that the establishment of carbapenem-resistant IC2 clones in the Philippines is likely the result of clonal expansion and geographical dissemination and at least partly explained by inadequate hospital infection control and prevention. This study is the first extensive genomic study of carbapenem-resistant A. baumannii in the Philippines and underscores the importance of hospital infection control and prevention to contain high-risk clones.

genomics↗

bioRxiv2020

Model-based inference of neutralizing antibody avidities against influenza virus

To assess the response to vaccination, quantity (concentration) and quality (avidity) of neutralizing antibodies are the most important parameters. Specifically, an increase in avidity indicates germinal center formation, which is required for establishing long-term protection. For influenza, the classical hemagglutination inhibition (HI) assay, however, quantifies a combination of both, and to separately determine avidity requires high experimental effort. We developed from first principles a biophysical model of hemagglutination inhibition to infer IgG antibody avidities from measured HI titers and IgG concentrations. The model accurately describes the relationship between neutralizing antibody concentration/avidity and HI titer, and explains quantitative aspects of the HI assay, such as robustness to pipetting errors and detection limit. We applied our model to infer avidities against the pandemic 2009 H1N1 influenza virus in vaccinated patients (n=45) after hematopoietic stem cell transplantation (HSCT) and validated our results with independent avidity measurements using an enzyme-linked immunosorbent assay with urea elution. Avidities inferred by the model correlated with experimentally determined avidities ({rho}=0.54, 95% CI=[0.31, 0.70], P<10-4). The model predicted that increases in IgG concentration mainly contribute to the observed HI titer increases in HSCT patients and that immunosuppressive treatment is associated with lower baseline avidities. Since our approach requires only easy-to-establish measurements as input, we anticipate that it will help to disentangle causes for poor vaccination outcomes also in larger patient populations. This study demonstrates that biophysical modelling can provide quantitative insights into agglutination assays and complement experimental measurements to refine antibody response analyses. Author SummaryInfluenza vaccines are assessed based on the induced antibody response, where antibody quantity (concentration) and antibody binding strength (avidity) determine the potency to neutralize the virus. In addition, an increase in avidity indicates a successful germinal center reaction, which is required for establishing long-term protection. However, the hemagglutination inhibition (HI) assay - traditionally used to assess influenza vaccines - measures a combination of both antibody concentration and avidity, and to separately determine avidity requires high experimental effort. We developed a biophysical model of the HI assay, which enables the inference of antibody avidities from measured HI titers and antibody concentrations. We applied our approach to a vaccinated population of immunocompromised patients after blood stem cell transplantation and validated our results experimentally. The model predicted that vaccination induced an increase in avidity in only a few patients and that patients under immunosuppressive treatment show lower baseline avidities. Since our approach requires only easily measurable data as input, it can facilitate the investigation of vaccine responses in larger populations. This study demonstrates that biophysical modelling can complement experimental data and provide additional details on agglutination experiments and antibody responses.

immunology↗

bioRxiv2020

Probabilistic Thermodynamic Analysis of Metabolic Networks

Random sampling of metabolic fluxes can provide an unbiased description of the capabilities of a metabolic network. However, current sampling approaches do not model thermodynamics explicitly, leading to inaccurate predictions of an organisms potential or actual metabolic operations. We present a probabilistic framework combining thermodynamic quantities with steady-state flux constraints to analyze the properties of a metabolic network. It includes methods for probabilistic metabolic optimization and for joint sampling of thermodynamic and flux spaces. Applied to a model of E. coli, we use the methods to reveal known and novel mechanisms of substrate channeling, and to accurately predict reaction directions and metabolite concentrations. Interestingly, predicted flux distributions are multimodal, leading to discrete hypotheses on E. coli s metabolic capabilities. C++ source code with MATLAB interface available at https://gitlab.com/csb.ethz/pta.

systems biology↗

bioRxiv2020

Scalable metabolic pathway analysis

The scope of application of genome-scale constraint-based models (CBMs) of metabolic networks rapidly expands toward multicellular systems. However, comprehensive analysis of CBMs through metabolic pathway analysis remains a major computational challenge because pathway numbers grow combinatorially with model sizes. Here, we define the minimal pathways (MPs) of a metabolic (sub)network as a subset of its elementary flux vectors. We enumerate or sample them efficiently using iterative minimization and a simple graph representation of MPs. These methods outperform the state of the art and they allow scalable pathway analysis for microbial and mammalian CBMs. Sampling random MPs from Escherichia colis central carbon metabolism in the context of a genome-scale CBM improves predictions of gene importance, and enumerating all minimal exchanges in a host-microbe model of the human gut predicts exchanges of metabolites associated with host-microbiota homeostasis and human health. MPs thereby open up new possibilities for the detailed analysis of large-scale metabolic networks.

systems biology↗

bioRxiv2020

Genomic Surveillance of Pseudomonas aeruginosa in the Philippines from 2013-2014

Pseudomonas aeruginosa is an opportunistic pathogen often causing nosocomial infections that are resilient to treatment due to an extensive repertoire of intrinsic and acquired resistance mechanisms. In recent years, increasing resistance rates to antibiotics such as carbapenems and extended-spectrum cephalosporins have been reported, as well as multi-drug resistant and possible extremely drug-resistant rates of approximately 21% and 15%, respectively. However, the molecular epidemiology and AMR mechanisms of this pathogen remains largely uncharacterized. We sequenced the whole genomes of 176 P. aeruginosa isolates collected in 2013-2014 by the Antimicrobial Resistance Surveillance Program. The multi-locus sequence type, presence of antimicrobial resistance (AMR) determinants, and relatedness between the isolates were derived from the sequence data. The concordance between phenotypic and genotypic resistance was also determined. Carbapenem resistance was associated namely with loss-of function of the OprD porin, and acquisition of the metallo-{beta}-lactamase VIM. The concordance between phenotypic and genotypic resistance was 93.27% overall for 6 antibiotics in 3 classes, but varied widely between aminoglycosides. The population of P. aeruginosa in the Philippines was diverse, with clonal expansions of XDR genomes belonging to multi-locus sequence types ST235, ST244, ST309, and ST773. We found evidence of persistence or reintroduction of the predominant clone ST235 in one hospital, as well as transfer between hospitals. Most of the ST235 genomes formed a distinct Philippine lineage when contextualized with international genomes, thus raising the possibility that this is a lineage unique to the Philippines. This was further supported by long-read sequencing of one representative XDR isolate, which revealed the presence of an integron carrying multiple resistance genes, including blaVIM-2, with differences in gene composition and synteny to other P. aeruginosa class 1 integrons described before. We produced the first comprehensive genomic survey of P. aeruginosa in the Philippines, which bridges the gap in genomic data from the Western Pacific region and will constitute the genetic background to contextualize ongoing prospective surveillance. Our results also highlight the importance of infection control interventions aimed to curtail the spread of international epidemic clone ST235 within the country.

genomics↗

bioRxiv2020

Genomic Surveillance of Methicillin-Resistant Staphylococcus aureus in the Philippines from 2013-2014

Methicillin Resistant Staphylococcus aureus (MRSA) remains one of the leading causes of both nosocomial and community infections worldwide. In the Philippines, MRSA rates have remained above 50% since 2010, but resistance to other antibiotics, including vancomycin, is low. The MRSA burden can be partially attributed to pathogen-specific characteristics of the circulating clones, but little was known about the S. aureus circulating clones in the Philippines. We sequenced the whole genomes of 116 S. aureus isolates collected in 2013-2014 by the Antimicrobial Resistance Surveillance Program. The multi-locus sequence type, spa type, SCC-mec type, presence of antimicrobial resistance (AMR) determinants and virulence genes, and relatedness between the isolates were all derived from the sequence data. The concordance between phenotypic and genotypic resistance was also determined. The MRSA population in the Philippines was composed of a limited number of genetic clones, including several international epidemic clones, such as CC30-spa-t019-SCCmec-IV-PVL+, CC5-SCCmec-typeIV, and ST239-spa-t030-SCCmec-typeIII. The CC30 genomes were related to the South West Pacific clone, but formed a distinct and diverse lineage, with evidence of global dissemination. We showed the independent acquisition of resistance to sulfamethoxazole/trimethoprim across different locations and genetic clones, but mostly in pediatric patients with invasive infections. The concordance between phenotypic and genotypic resistance was 99.68% overall for 8 antibiotics in 7 classes. We produced the first comprehensive genomic survey of S. aureus in the Philippines, which bridges the gap in genomic data from the Western Pacific region and will constitute the genetic background to contextualize ongoing prospective surveillance.

genomics↗

bioRxiv2020

Genomic Surveillance of Neisseria gonorrhoeae in the Philippines from 2013-2014

Antimicrobial-resistant Neisseria gonorrhoeae is a major threat to public health and is of particular concern in the Western Pacific Region, where the incidence of gonorrhoea is high. The Antimicrobial Resistance Surveillance Program (ARSP) has been capturing information on resistant gonorrhoea since 1996, but genomic epidemiology studies on this pathogen are lacking in the Philippines. We sequenced the whole genomes of 21 N. gonorrhoeae isolates collected in 2013-2014 by the ARSP. The multilocus sequence type, multiantigen sequence type, presence of determinants of antimicrobial resistance and relatedness among the isolates were all derived from the sequence data. The concordance between phenotypic and genotypic resistance was also determined. Ten of 21 isolates were resistant to penicillin, ciprofloxacin and tetracycline, due mainly to the presence of blaTEM gene, the S91F mutation in the gyrA gene and the tetM gene, respectively. None of the isolates was resistant to ceftriaxone or cefixime. The concordance between phenotypic and genotypic resistance was 92.38% overall for five antibiotics in four classes. Despite the small number of isolates studied, they were genetically diverse, as shown by the sequence types, the N. gonorrhoeae multiantigen sequence typing types and the tree. Comparison with global genomes placed the Philippine genomes within global lineage A and led to identification of an international transmission route. This first genomic survey of N. gonorrhoeae isolates collected by ARSP will be used to contextualize prospective surveillance. It highlights the importance of genomic surveillance in the Western Pacific and other endemic regions for understanding the spread of drug-resistant gonorrhoea worldwide.

genomics↗

bioRxiv2020

Comparison of de-duplication methods used by WHO Global Antimicrobial Resistance Surveillance System (GLASS) and Japan Nosocomial Infections Surveillance (JANIS) in the surveillance of antimicrobial resistance

A major issue in the surveillance of antimicrobial resistance (AMR) is "de-duplication" or removal of repeated isolates, for which there exist multiple methods. The World Health Organization (WHO) Global Antimicrobial Resistance Surveillance System (GLASS) requires de-duplication by selecting only the first isolate of a given bacterial species per patient per surveillance period per specimen type per age group, gender, and infection origin stratification. However, no study on the comparative application of this method has been reported. The objective of this study was to evaluate differences in data tabulation between the WHO GLASS and the Japan Nosocomial Infections Surveillance (JANIS) system, which counts both patients and isolates after removing repeated isolates of the same bacterial species per multiresistance phenotype isolated from a patient within 30 days, regardless of specimen type. All bacterial data, consisting of approximately 8 million samples from 1795 Japanese hospitals in 2017 were exported from the JANIS database, and were tabulated using either the de-duplication algorithm of GLASS, or JANIS. We compared the tabulated results of the total number of patients whose blood and urine cultures were taken and of the percentage of resistant isolates of Escherichia coli for each priority antibiotic. The number of patients per specimen type tabulated by the JANIS method was always smaller than that of GLASS. There was a small (< 3%) difference in the percentage of resistance of E. coli for any antibiotic between the two methods in both out- and inpatient settings and blood and urine isolates. The two tabulation methods did not show considerable differences in terms of the tabulated percentages of resistance for E. coli. We further discuss how the use of GLASS tabulations to create a public software and website that could help to facilitate the understanding of and treatment against AMR.

microbiology↗