Artificial Intelligence in Battle against Antimicrobial Resistance: Opportunities and Challenges

Due to the overuse and abuse of antibiotics, antimicrobial resistance (AMR) poses a serious risk to socioeconomic development and public health. A paradigm shift is required to address this dilemma, and artificial intelligence (AI) appears as a possible remedy. AI, including machine learning (ML) and deep learning (DL), has demonstrated significant promise in several medical research fields, especially in the fight against AMR. Applications of AI in AMR use cutting-edge computational methods to analyze gene expression and whole-genome sequencing data, assisting in discovering infectious disease etiology and disease subtypes. These AI-driven systems have several advantages over more conventional ones, including less need for human involvement, more accuracy, and lower costs. However, they also encounter difficulties, such as inconsistent performance across datasets, with data volume critically influencing model efficacy. The accessibility and expense of high-throughput sequencing data, particularly next-generation sequencing data, also pose challenges to the wider application of AI models for AMR investigation. Despite these difficulties, AI has significant promise in the fight against AMR, and its advantages and disadvantages must be carefully considered in order to build successful tactics for dealing with this urgent worldwide problem. We assess research papers on AMR analysis using AI on various datasets and contrast the effectiveness of various AI models. We thoroughly reviewed the DL models used up to this point in the field of AMR, and we additionally discussed the challenges that come with deploying these approaches. This paper offers a thorough overview of AI's applications in AMR analysis, highlighting both its benefits and drawbacks

Genomic insights into the rapid emergence and evolution of MDR in Staphylococcus pseudintermedius.

OBJECTIVES: MDR methicillin-resistant Staphylococcus pseudintermedius (MRSP) strains have emerged rapidly as major canine pathogens and present serious treatment issues and concerns to public health due to their, albeit low, zoonotic potential. A further understanding of the genetics of resistance arising from a broadly susceptible background of S. pseudintermedius is needed. METHODS: We sequenced the genomes of 12 S. pseudintermedius isolates of varied STs and resistance phenotypes. RESULTS: Nine distinct clonal lineages had acquired either staphylococcal cassette chromosome (SCC) mec elements and/or Tn5405-like elements carrying up to five resistance genes [aphA3, sat, aadE, erm(B), dfrG] to generate MRSP, MDR methicillin-susceptible S. pseudintermedius and MDR MRSP populations. The most successful and clinically problematic MDR MRSP clones, ST68 SCCmecV(T) and ST71 SCCmecII-III, have further accumulated mutations in gyrA and grlA conferring resistance to fluoroquinolones. The carriage of additional mobile genetic elements (MGEs) was highly variable, suggesting that horizontal gene transfer is frequent in S. pseudintermedius populations. CONCLUSIONS: Importantly, the data suggest that MDR MRSP evolved rapidly by the acquisition of a very limited number of MGEs and mutations, and that the use of many classes of antimicrobials may co-select for the spread and emergence of MDR and XDR strains. Antimicrobial stewardship will need to be comprehensive, encompassing human medicine and veterinary disciplines to successfully preserve antimicrobial efficacy

Resistome Identification from Whole Genome Sequencing Data of Norwegian Isolates

Masters in Applied and Commercial Biotechnology. Inland Norway University of Applied Sciences. Faculty of Applied Ecology, Agricultural sciences and BiotechnologyAntimicrobial resistance (AMR) is considered a potential threat to global health. Norway have had a low prevalence of resistant bacteria. But in the recent years there has been an increase in resistant bacteria including, Escherichia coli, Klebsiella pneumoniae and Acinetobacter baumannii. Traditionally, clinical microbiology has used culture-based techniques to determine antimicrobial susceptibility and resistance profiles, but now whole–genome sequencing for antibiotic susceptibility (WGS-AST) has emerged as a potential alternative. We aimed to investigate the prevalence of antimicrobial resistance genes and plasmids in WGS of 111 clinical Norwegian isolates of E. coli, K. pneumoniae, and A. baumannii, to identify correlations between phenotypic and genotypic resistance in the isolates, which are related to antibiotic resistance to β-lactam, aminoglycosides, fluoroquinolone, trimethoprim, tetracycline, and phenicol. The most occurring drug class was β-lactam antibiotic with TEM (38%) in E.coli, SHV (67%) in K. pneumoniae, and OXA (100%) and TEM (45%) gene families in A. baumannii. In silico detection of plasmids with Brooks et al database showed plasmid p2_000837 as prominent plasmid 12% E.coli isolates. There were four plasmids (pIB_NDM_1, p2_W5-6, pCHL5009T-102k-mcr3, pVir_020022) in 2% K. pneumoniae isolates which were also shared with E. coli. Only one plasmid (pHZ23-1-1) was confirmed in 9% of A. baumannii isolates. PLSDB detected Plasmid A and plasmid 4 with the maximum percentage in E.coli (10%) and K. pneumoniae isolates (4%). In E. coli and K. pneumoniae, the presence of incompatibility groups was observed; IncFIB (64% and 27%), Col156 (74% and 27%), IncFII (43% and 15%), while IncHI-1B(pNDM-MAR) (12%) were present only in K. pneumoniae . A total of 75 isolates had resistance to the tested β-lactam antibiotics, out of which 63 had the corresponding resistance genes (ampC, SHV, CTX-M, TEM, LEN, OXA). Only 11 E.coli and one K. pneumoniae isolates were found to have resistance genes and the plasmids on the same node to confirm plasmid mediated resistance. This study demonstrates the utility of WGS in defining resistance elements and highlights the diversity of resistance within the selected isolates to further the diagnostics and therapeutics for the treatment of the relevant infections

Techniques to Improve Deep Learning for Phenotype Prediction from Genotype Data

We show that by representing Single Nucleotide Polymorphism (SNP) data to a neural network in a way that incorporates quality scores and avoids filtering out low quality SNPs we are able to increase the effectiveness of a deep neural network for phenotype prediction from genotype in some cases. We also show that we are able to significantly increase the predictive power of a neural network by making use of transfer learning. We demonstrate these results on a Whole Genome Sequencing (WGS) Neisseria gonorrhoeae dataset where we predict Antimicrobial Resistance (AMR) as well as on an exome sequencing Lens culinaris dataset where we predict 3 growing rate phenotypes

Large genomic differences between Moraxella bovoculi isolates acquired from the eyes of cattle with infectious bovine keratoconjunctivitis versus the deep nasopharynx of asymptomatic cattle

Citation: Dickey, A. M., Loy, J. D., Bono, J. L., Smith, T. P. L., Apley, M. D., Lubbers, B. V., . . . Clawson, M. L. (2016). Large genomic differences between Moraxella bovoculi isolates acquired from the eyes of cattle with infectious bovine keratoconjunctivitis versus the deep nasopharynx of asymptomatic cattle. Veterinary Research, 47, 11. doi:10.1186/s13567-016-0316-2Moraxella bovoculi is a recently described bacterium that is associated with infectious bovine keratoconjunctivitis (IBK) or "pinkeye" in cattle. In this study, closed circularized genomes were generated for seven M. bovoculi isolates: three that originated from the eyes of clinical IBK bovine cases and four from the deep nasopharynx of asymptomatic cattle. Isolates that originated from the eyes of IBK cases profoundly differed from those that originated from the nasopharynx of asymptomatic cattle in genome structure, gene content and polymorphism diversity and consequently placed into two distinct phylogenetic groups. These results suggest that there are genetically distinct strains of M. bovoculi that may not associate with IBK

Pneumococcal within-host diversity during colonization, transmission and treatment

Characterizing the genetic diversity of pathogens within the host promises to greatly improve surveillance and reconstruction of transmission chains. For bacteria, it also informs our understanding of inter-strain competition and how this shapes the distribution of resistant and sensitive bacteria. Here we study the genetic diversity of Streptococcus pneumoniae within 468 infants and 145 of their mothers by deep sequencing whole pneumococcal populations from 3,761 longitudinal nasopharyngeal samples. We demonstrate that deep sequencing has unsurpassed sensitivity for detecting multiple colonization, doubling the rate at which highly invasive serotype 1 bacteria were detected in carriage compared with gold-standard methods. The greater resolution identified an elevated rate of transmission from mothers to their children in the first year of the child's life. Comprehensive treatment data demonstrated that infants were at an elevated risk of both the acquisition and persistent colonization of a multidrug-resistant bacterium following antimicrobial treatment. Some alleles were enriched after antimicrobial treatment, suggesting that they aided persistence, but generally purifying selection dominated within-host evolution. Rates of co-colonization imply that in the absence of treatment, susceptible lineages outcompeted resistant lineages within the host. These results demonstrate the many benefits of deep sequencing for the genomic surveillance of bacterial pathogens. Longitudinal population deep sequencing of Streptococcus pneumoniae sampled from infants and their mothers improves our understanding of the dynamics of colonization, transmission, inter-strain competition and the impact of antibiotic treatment.Peer reviewe

Genomic Insights of a Methicillin-Resistant Biofilm-Producing Staphylococcus aureus Strain Isolated From Food Handlers.

Methicillin-resistant Staphylococcus aureus (MRSA) is an important zoonotic pathogen associated with a wide range of infections in humans and animals. Thus, the emergence of MRSA clones poses an important threat to human and animal health. This study is aimed at elucidating the genomics insights of a strong biofilm-producing and multidrug-resistant (MDR) S. aureus MTR_BAU_H1 strain through whole-genome sequencing (WGS). The S. aureus MTR_BAU_H1 strain was isolated from food handlers hand swabs in Bangladesh and phenotypically assessed for antimicrobial susceptibility and biofilm production assays. The isolate was further undergone to high throughput WGS and analysed using different bioinformatics tools to elucidate the genetic diversity, molecular epidemiology, sequence type (ST), antimicrobial resistance, and virulence gene distribution. Phenotypic analyses revealed that the S. aureus MTR_BAU_H1 strain is a strong biofilm-former and carries both antimicrobial resistance (e.g., methicillin resistance; mecA, beta-lactam resistance; blaZ and tetracycline resistance; tetC) and virulence (e.g., sea, tsst, and PVL) genes. The genome of the S. aureus MTR_BAU_H1 belonged to ST1930 that possessed three plasmid replicons (e.g., rep16, rep7c, and rep19), seven prophages, and two clustered regularly interspaced short palindromic repeat (CRISPR) arrays of varying sizes. Phylogenetic analysis showed a close evolutionary relationship between the MTR_BAU_H1 genome and other MRSA clones of diverse hosts and demographics. The MTR_BAU_H1 genome harbours 42 antimicrobial resistance genes (ARGs), 128 virulence genes, and 273 SEED subsystems coding for the metabolism of amino acids, carbohydrates, proteins, cofactors, vitamins, minerals, and lipids. This is the first-ever WGS-based study of a strong biofilm-producing and MDR S. aureus strain isolated from human hand swabs in Bangladesh that unveils new information on the resistomes (ARGs and correlated mechanisms) and virulence potentials that might be linked to staphylococcal pathogenesis in both humans and animals

Mobile genetic elements causing plasticity in E. faecium

The paper 3 of this thesis is not available in Munin. Paper 3: Sivertsen, A., Pedersen, T., Janice, J., Hegstad, K.: “The Enterococcus Cassette Chromosome: an SCCmec-like mobilisable element”. (Manuscript).I helseinstitusjoner vancomycin-resistente enterokokker en fryktet bakterie som kan lage alvorlig infeksjonssykdom i pasienter med dårlig immunforsvar, og er vanskelig å behandle. Avhandlingen fokuserer på vancomycin-resistente enterokokker (VRE), og hvordan disse bakteriene gjennom å overføre gener mellom hverandre kan utvikle resistens mot antibiotika. Vi har analysert to utbrudd av VRE i Sverige og i Norge, og har funnet at VRE kan være på vei til å bli et mer vanlig patogen i skandinaviske sykehus. Dagens diagnostiske verktøy er ikke i stand til å fange opp alle typer VRE. Dette har konsekvenser for både diagnostikk, resistensovervåkning og risiko for feilbehandling av svært syke pasienter. Nye gensekvenseringsteknologier kan forbedre denne type diagnostikk ved å kunne se på genotypen i tillegg, noe som er viktig da vancomycinresistensgener kan være tilstede i bakterien uten at bakterien har fenotype for dette. I begge utbruddene var diagnostikken utilfredsstillende, da bakterien kunne bli tolket som følsom. I det ene utbruddet utviklet VRE resistens under behandling på grunn av for eksempel mobile genetiske elementer kalt IS-elementer hoppet rundt i vancomycinresistensgenene og påvirket uttrykket deres. Resultater fra doktorgraden har allerede ført til en endring i rådgiving på diagnostikk av VRE hos svært syke pasienter. Vi har også funnet at mobile genetiske elementer (MGE), DNA-et som flytter seg mellom bakterier, har en stor evne til å rekombinere seg og danne varianter med ulikt geninnhold. Inntil nå har strukturen på disse elementene vært vanskelig å rekonstruere. Dermed har betydningen av MGE’er for bakterienes resistenspotensiale vært vanskelig å vurdere. Man kan observere at disse elementene oppfører seg som Babushka-dukker ved å koble seg på hverandre. Såkalte long-read sekvenseringsmetoder er i stand til å rekonstruere strukturen på slike elementer, og det at de kun har vært kommersielt tilgjengelige de siste 3-4 år gjør at der fortsatt er mye å lære om mobile genetiske elementer og deres innvirkning på resistensutvikingen av bakterier