scholarly journals Precise prediction of antibiotic resistance in Escherichia coli from full genome sequences

2018 ◽  
Author(s):  
Danesh Moradigaravand ◽  
Martin Palm ◽  
Anne Farewell ◽  
Ville Mustonen ◽  
Jonas Warringer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Antibiotic Resistance ◽  
Population Structure ◽  
Genome Sequencing ◽  
Diagnostic Tools ◽  
Clinical Settings ◽  
Whole Genome ◽  
Genome Sequences ◽  
E Coli ◽  
Resistant Strains

AbstractThe emergence of microbial antibiotic resistance is a global health threat. In clinical settings, the key to controlling spread of resistant strains is accurate and rapid detection. As traditional culture-based methods are time consuming, genetic approaches have recently been developed for this task. The diagnosis is typically made by measuring a few known determinants previously identified from whole genome sequencing, and thus is restricted to existing information on biological mechanisms. To overcome this limitation, we employed machine learning models to predict resistance to 11 compounds across four classes of antibiotics from existing and novel whole genome sequences of 1936 E. coli strains. We considered a range of methods, and examined population structure, isolation year, gene content, and polymorphism information as predictors. Gradient boosted decision trees consistently outperformed alternative models with an average F1 score of 0.88 on held-out data (range 0.66-0.96). While the best models most frequently employed all inputs, an average F1 score of 0.73 could be obtained using population structure information alone. Single nucleotide variation data were less useful, and failed to improve prediction for ten out of 11 antibiotics. These results demonstrate that antibiotic resistance in E. coli can be accurately predicted from whole genome sequences without a priori knowledge of mechanisms, and that both genomic and epidemiological data are informative. This paves way to integrating machine learning approaches into diagnostic tools in the clinic.SummaryOne of the major health threats of 21st century is emergence of antibiotic resistance. To manage its economic impact, efforts are made to develop novel diagnostic tools that rapidly detect resistant strains in clinical settings. In our study, we employed a range machine learning tools to predict antibiotic resistance from whole genome sequencing data for E. coli. We used the presence or absence of genes, population structure and isolation year of isolates as predictors, and could attain average precision of 0.93 and recall of 0.83, without prior knowledge about the causal mechanisms. These results demonstrate the potential application of machine learning methods as a diagnostic tool in healthcare settings.

scholarly journals Development of evolution drugs - antibacterial compounds that block pathways to resistance

2020 ◽  
Author(s):  
Yanmin Zhang ◽  
Sourav Chowdhury ◽  
João V. Rodrigues ◽  
Eugene Shakhnovich
Keyword(s):  
Antibiotic Resistance ◽  
Dihydrofolate Reductase ◽  
Experimental Approach ◽  
Whole Genome ◽  
Bacterial Protein ◽  
Antibacterial Compounds ◽  
E Coli ◽  
Resistant Strains ◽  
Resistant Mutants

AbstractAntibiotic resistance is a worldwide challenge. A potential approach to block resistance is to simultaneously inhibit WT and known escape variants of the target bacterial protein. Here we applied an integrated computational and experimental approach to discover compounds that inhibit both WT and trimethoprim (TMP) resistant mutants of E. coli dihydrofolate reductase (DHFR). We identified a novel compound (CD15-3) that inhibits WT DHFR and its TMP resistant variants L28R, P21L and A26T with IC50 50-75 μM against WT and TMP-resistant strains. Resistance to CD15-3 was dramatically delayed compared to TMP in in vitro evolution. Whole genome sequencing of CD15-3 resistant strains showed no mutations in the target folA locus. Rather, gene duplication of several efflux pumps gave rise to weak (about twofold increase in IC50) resistance against CD15-3. Altogether, our results demonstrate the promise of strategy to develop evolution drugs - compounds which block evolutionary escape routes in pathogens.

scholarly journals Whole-genome sequencing-based phylogeny, antibiotic resistance, and invasive phenotype of Escherichia coli strains colonizing the cervix of women in preterm labor

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Marvin Williams ◽  
Alyssa B. Jones ◽  
Amanda L. Maxedon ◽  
Jennifer E. Tabakh ◽  
Cindy B. McCloskey ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Antibiotic Resistance ◽  
Epithelial Cells ◽  
Pregnant Women ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Preterm Labor ◽  
Whole Genome ◽  
E Coli ◽  
Resistance Traits

Abstract Background Escherichia coli is a major neonatal pathogen and the leading cause of early-onset sepsis in preterm newborns. Maternal E. coli strains are transmitted to the newborn causing invasive neonatal disease. However, there is a lack of data regarding the phenotypic and genotypic characterization of E. coli strains colonizing pregnant women during labor. Methods This prospective study performed at the University of Oklahoma Medical Center (OUHSC) from March 2014 to December 2015, aimed to investigate the colonization rate, and the phylogeny, antibiotic resistance traits, and invasive properties of E. coli strains colonizing the cervix of fifty pregnant women diagnosed with preterm labor (PTL). Molecular analyses including bacterial whole-genome sequencing (WGS), were performed to examine phylogenetic relationships among the colonizing strains and compare them with WGS data of representative invasive neonatal E. coli isolates. Phenotypic and genotypic antibiotic resistance traits were investigated. The bacteria’s ability to invade epithelial cells in vitro was determined. Results We recruited fifty women in PTL. Cervical samples yielded E. coli in 12 % (n=6). The mean gestational age was 32.5 (SD±3.19) weeks. None delivered an infant with E. coli disease. Phenotypic and genotypic antibiotic resistance testing did not overall demonstrate extensive drug resistance traits among the cervical E. coli isolates, however, one isolate was multi-drug resistant. The isolates belonged to five different phylogroups, and WGS analyses assigned each to individual multi-locus sequence types. Single nucleotide polymorphism-based comparisons of cervical E. coli strains with six representative neonatal E. coli bacteremia isolates demonstrated that only half of the cervical E. coli isolates were phylogenetically related to these neonatal invasive strains. Moreover, WGS comparisons showed that each cervical E. coli isolate had distinct genomic regions that were not shared with neonatal E. coli isolates. Cervical and neonatal E. coli isolates that were most closely related at the phylogenetic level had similar invasion capacity into intestinal epithelial cells. In contrast, phylogenetically dissimilar cervical E. coli strains were the least invasive among all isolates. Conclusions This pilot study showed that a minority of women in PTL were colonized in the cervix with E. coli, and colonizing strains were not phylogenetically uniformly representative of E. coli strains that commonly cause invasive disease in newborns. Larger studies are needed to determine the molecular characteristics of E. coli strains colonizing pregnant women associated with an increased risk of neonatal septicemia.

scholarly journals Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning

2019 ◽  
Author(s):  
Bálint Ármin Pataki ◽  
Sébastien Matamoros ◽  
Boas C.L. van der Putten ◽  
Daniel Remondini ◽  
Enrico Giampieri ◽  
...  
Keyword(s):  
Machine Learning ◽  
Escherichia Coli ◽  
Minimum Inhibitory Concentration ◽  
Antimicrobial Resistance ◽  
Genome Sequencing ◽  
Inhibitory Concentration ◽  
Whole Genome ◽  
Wild Type ◽  
Sequencing Data ◽  
E Coli

2.AbstractA possible way to tackle the crisis of antimicrobial resistance development is a strict policy when prescribing antibiotics. Thus, it is important that prescriptions are based on antimicrobial susceptibility data to ensure effective treatment outcomes. The increasing availability of next-generation sequencing (NGS), bacterial whole genome sequencing (WGS) can facilitate a more reliable and faster alternative to traditional phenotyping for the detection and surveillance of AMR.This work proposes a machine learning approach that can predict the minimum inhibitory concentration (MIC) for a given antibiotic, here ciprofloxacin, on the basis of both genome-wide mutation profiles and profiles of acquired antimicrobial resistance genes (ARG). We analysed 704 Escherichia coli genomes combined with their respective MIC measurements for ciprofloxacin originating from different countries. The four most important predictors found by the model, mutations in gyrA residues Ser83 and Asp87, a mutation in parC residue Ser80 and presence of any qnrS gene, have been experimentally validated before. Using only these four predictors in a linear regression model, 65% and 92% of the test samples’ MIC were correctly predicted within a two- and a four-fold dilution range, respectively. The presented work goes further than the typical predictions that use machine learning as a black box model concept. The recent progress in WGS technology in combination with machine learning analysis approaches indicates that in the near future WGS of bacteria might become cheaper and faster than a MIC measurement.3.Impact statementWhole genome sequencing has become the standard approach to study molecular epidemiology of bacteria. However, the application of WGS in the clinical microbiology laboratory as part of individual patient diagnostics still requires significant steps forward, in particular with respect to prediction of antibiotic susceptibility based on DNA sequence. Whilst the majority of studies of prediction of susceptibility have used a binary outcome (susceptible/resistant), a quantitative prediction of susceptibility, such as the MIC, will allow for earlier detection of trends in increasing resistance as well as the flexibility to follow potential adjustments in definitions of susceptible (wild type) and resistant (non-wild type) categories (breakpoints/ epidemiological cut-off values).4.Data summaryIn this study, 704 E. coli genomes combined with MIC measurement for ciprofloxacin were analysed (24). Paired-end sequencing was performed on all isolates and the results were stored in FASTQ format. The isolates originated from five countries, Denmark, Italy, USA, UK, and Vietnam. The MIC distribution for these isolates is depicted in Table 1. Out of 704, 266 E. coli genomes had no country metadata available and were used as an independent test set. All data were deposited in the AMR Data Hub (24) which consists of raw sequencing data, ciprofloxacin minimum inhibitory concentrations, and additional metadata such as the origin of the samples.TABLE 1The collected and used data in the analysis grouped by country and MIC values.Publicly available sequencing data was used from projects PRJEB21131, PRJNA266657, PRJNA292901, PRJNA292904, PRJNA292902, PRJDB7087, PRJEB21880, PRJEB21997, PRJEB14086 and PRJEB16326.Download and analysis scripts are available at https://github.com/patbaa/AMR_ciprofloxacin. iTOL phylogenetic tree is available at https://itol.embl.de/tree/14511722611491391569485969.The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

scholarly journals Genomic diversity of Escherichia coli isolates from non-human primates in the Gambia

2020 ◽  
Author(s):  
Ebenezer Foster-Nyarko ◽  
Nabil-Fareed Alikhan ◽  
Anuradha Ravi ◽  
Gaëtan Thilliez ◽  
Nicholas Thomson ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Population Structure ◽  
Antimicrobial Resistance ◽  
Genome Sequencing ◽  
Host Species ◽  
The Gambia ◽  
Genomic Diversity ◽  
Whole Genome ◽  
E Coli ◽  
Sequence Types

AbstractIncreasing contact between humans and non-human primates provides an opportunity for the transfer of potential pathogens or antimicrobial resistance between host species. We have investigated genomic diversity, and antimicrobial resistance in Escherichia coli isolates from four species of non-human primate in the Gambia: Papio papio (n=22), Chlorocebus sabaeus (n=14), Piliocolobus badius (n=6) and Erythrocebus patas (n=1). We performed Illumina whole-genome sequencing on 101 isolates from 43 stools, followed by nanopore long-read sequencing on eleven isolates. We identified 43 sequence types (STs) by the Achtman scheme (ten of which are novel), spanning five of the eight known phylogroups of E. coli. The majority of simian isolates belong to phylogroup B2—characterised by strains that cause human extraintestinal infections—and encode factors associated with extraintestinal disease. A subset of the B2 strains (ST73, ST681 and ST127) carry the pks genomic island, which encodes colibactin, a genotoxin associated with colorectal cancer. We found little antimicrobial resistance and only one example of multi-drug resistance among the simian isolates. Hierarchical clustering showed that simian isolates from ST442 and ST349 are closely related to isolates recovered from human clinical cases (differences in 50 and seven alleles respectively), suggesting recent exchange between the two host species. Conversely, simian isolates from ST73, ST681 and ST127 were distinct from human isolates, while five simian isolates belong to unique core-genome ST complexes—indicating novel diversity specific to the primate niche. Our results are of public health importance, considering the increasing contact between humans and wild non-human primates.Impact statementLittle is known about the population structure, virulence potential and the burden of antimicrobial resistance among Escherichia coli from wild non-human primates, despite increased exposure to humans through the fragmentation of natural habitats. Previous studies, primarily involving captive animals, have highlighted the potential for bacterial exchange between non-human primates and humans living nearby, including strains associated with intestinal pathology. Using multiple-colony sampling and whole-genome sequencing, we investigated the strain distribution and population structure of E. coli from wild non-human primates from the Gambia. Our results indicate that these monkeys harbour strains that can cause extraintestinal infections in humans. We document the transmission of virulent E. coli strains between monkeys of the same species sharing a common habitat and evidence of recent interaction between strains from humans and wild non-human primates. Also, we present complete genome assemblies for five novel sequence types of E. coli.Author notesAll supporting data, code and protocols have been provided within the article or through supplementary data files. Nine supplementary figures and six supplementary files are available with the online version of this article.AbbreviationsExPEC, Extraintestinal pathogenic Escherichia coli; ST, Sequence type; AMR, Antimicrobial resistance; MLST, Multi-locus sequence typing; VFDB, Virulence factors database; SNP, single nucleotide polymorphism; SPRI, Solid phase reversible immobilisation.Data summaryThe raw sequences and polished assemblies from this study are available in the National Center for Biotechnology Information (NCBI) Short Read Archive, under the BioProject accession number PRJNA604701. The full list and characteristics of these strains and other reference strains used in the analyses are presented in Table 1 and Supplementary Files 1-4 (available with the online version of this article).

scholarly journals Expanding U.S. Laboratory Capacity for Neisseria gonorrhoeae Antimicrobial Susceptibility Testing and Whole-Genome Sequencing through the CDC's Antibiotic Resistance Laboratory Network

2020 ◽  
Vol 58 (4) ◽  
Author(s):  
Ellen N. Kersh ◽  
Cau D. Pham ◽  
John R. Papp ◽  
Robert Myers ◽  
Richard Steece ◽  
...  
Keyword(s):  
Public Health ◽  
Antibiotic Resistance ◽  
Neisseria Gonorrhoeae ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Antimicrobial Susceptibility ◽  
Susceptibility Testing ◽  
Whole Genome ◽  
Content Type ◽  
Laboratory Capacity

ABSTRACT U.S. gonorrhea rates are rising, and antibiotic-resistant Neisseria gonorrhoeae (AR-Ng) is an urgent public health threat. Since implementation of nucleic acid amplification tests for N. gonorrhoeae identification, the capacity for culturing N. gonorrhoeae in the United States has declined, along with the ability to perform culture-based antimicrobial susceptibility testing (AST). Yet AST is critical for detecting and monitoring AR-Ng. In 2016, the CDC established the Antibiotic Resistance Laboratory Network (AR Lab Network) to shore up the national capacity for detecting several resistance threats including N. gonorrhoeae. AR-Ng testing, a subactivity of the CDC’s AR Lab Network, is performed in a tiered network of approximately 35 local laboratories, four regional laboratories (state public health laboratories in Maryland, Tennessee, Texas, and Washington), and the CDC’s national reference laboratory. Local laboratories receive specimens from approximately 60 clinics associated with the Gonococcal Isolate Surveillance Project (GISP), enhanced GISP (eGISP), and the program Strengthening the U.S. Response to Resistant Gonorrhea (SURRG). They isolate and ship up to 20,000 isolates to regional laboratories for culture-based agar dilution AST with seven antibiotics and for whole-genome sequencing of up to 5,000 isolates. The CDC further examines concerning isolates and monitors genetic AR markers. During 2017 and 2018, the network tested 8,214 and 8,628 N. gonorrhoeae isolates, respectively, and the CDC received 531 and 646 concerning isolates and 605 and 3,159 sequences, respectively. In summary, the AR Lab Network supported the laboratory capacity for N. gonorrhoeae AST and associated genetic marker detection, expanding preexisting notification and analysis systems for resistance detection. Continued, robust AST and genomic capacity can help inform national public health monitoring and intervention.

scholarly journals Whole Genome Sequencing Refines Knowledge on the Population Structure of Mycobacterium bovis from a Multi-Host Tuberculosis System

2021 ◽  
Vol 9 (8) ◽  
pp. 1585
Author(s):  
Ana C. Reis ◽  
Liliana C. M. Salvador ◽  
Suelee Robbe-Austerman ◽  
Rogério Tenreiro ◽  
Ana Botelho ◽  
...  
Keyword(s):  
Population Structure ◽  
Whole Genome Sequencing ◽  
Wild Boar ◽  
Genome Sequencing ◽  
Mycobacterium Bovis ◽  
Red Deer ◽  
Variable Number Tandem Repeat ◽  
Variant Calling ◽  
Whole Genome ◽  
Network Analyses

Classical molecular analyses of Mycobacterium bovis based on spoligotyping and Variable Number Tandem Repeat (MIRU-VNTR) brought the first insights into the epidemiology of animal tuberculosis (TB) in Portugal, showing high genotypic diversity of circulating strains that mostly cluster within the European 2 clonal complex. Previous surveillance provided valuable information on the prevalence and spatial occurrence of TB and highlighted prevalent genotypes in areas where livestock and wild ungulates are sympatric. However, links at the wildlife–livestock interfaces were established mainly via classical genotype associations. Here, we apply whole genome sequencing (WGS) to cattle, red deer and wild boar isolates to reconstruct the M. bovis population structure in a multi-host, multi-region disease system and to explore links at a fine genomic scale between M. bovis from wildlife hosts and cattle. Whole genome sequences of 44 representative M. bovis isolates, obtained between 2003 and 2015 from three TB hotspots, were compared through single nucleotide polymorphism (SNP) variant calling analyses. Consistent with previous results combining classical genotyping with Bayesian population admixture modelling, SNP-based phylogenies support the branching of this M. bovis population into five genetic clades, three with apparent geographic specificities, as well as the establishment of an SNP catalogue specific to each clade, which may be explored in the future as phylogenetic markers. The core genome alignment of SNPs was integrated within a spatiotemporal metadata framework to further structure this M. bovis population by host species and TB hotspots, providing a baseline for network analyses in different epidemiological and disease control contexts. WGS of M. bovis isolates from Portugal is reported for the first time in this pilot study, refining the spatiotemporal context of TB at the wildlife–livestock interface and providing further support to the key role of red deer and wild boar on disease maintenance. The SNP diversity observed within this dataset supports the natural circulation of M. bovis for a long time period, as well as multiple introduction events of the pathogen in this Iberian multi-host system.

scholarly journals Assessing genomic diversity and signatures of selection in Jiaxian Red cattle using whole-genome sequencing data

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xiaoting Xia ◽  
Shunjin Zhang ◽  
Huaju Zhang ◽  
Zijing Zhang ◽  
Ningbo Chen ◽  
...  
Keyword(s):  
Population Structure ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genomic Variation ◽  
Genomic Diversity ◽  
System Response ◽  
Whole Genome ◽  
Population Structure Analysis ◽  
Native Cattle ◽  
Genomic Regions

Abstract Background Native cattle breeds are an important source of genetic variation because they might carry alleles that enable them to adapt to local environment and tough feeding conditions. Jiaxian Red, a Chinese native cattle breed, is reported to have originated from crossbreeding between taurine and indicine cattle; their history as a draft and meat animal dates back at least 30 years. Using whole-genome sequencing (WGS) data of 30 animals from the core breeding farm, we investigated the genetic diversity, population structure and genomic regions under selection of Jiaxian Red cattle. Furthermore, we used 131 published genomes of world-wide cattle to characterize the genomic variation of Jiaxian Red cattle. Results The population structure analysis revealed that Jiaxian Red cattle harboured the ancestry with East Asian taurine (0.493), Chinese indicine (0.379), European taurine (0.095) and Indian indicine (0.033). Three methods (nucleotide diversity, linkage disequilibrium decay and runs of homozygosity) implied the relatively high genomic diversity in Jiaxian Red cattle. We used θπ, CLR, FST and XP-EHH methods to look for the candidate signatures of positive selection in Jiaxian Red cattle. A total number of 171 (θπ and CLR) and 17 (FST and XP-EHH) shared genes were identified using different detection strategies. Functional annotation analysis revealed that these genes are potentially responsible for growth and feed efficiency (CCSER1), meat quality traits (ROCK2, PPP1R12A, CYB5R4, EYA3, PHACTR1), fertility (RFX4, SRD5A2) and immune system response (SLAMF1, CD84 and SLAMF6). Conclusion We provide a comprehensive overview of sequence variations in Jiaxian Red cattle genomes. Selection signatures were detected in genomic regions that are possibly related to economically important traits in Jiaxian Red cattle. We observed a high level of genomic diversity and low inbreeding in Jiaxian Red cattle. These results provide a basis for further resource protection and breeding improvement of this breed.

scholarly journals E. coli NF73-1 Isolated From NASH Patients Aggravates NAFLD in Mice by Translocating Into the Liver and Stimulating M1 Polarization

2020 ◽  
Vol 10 ◽  
Author(s):  
Yifan Zhang ◽  
Weiwei Jiang ◽  
Jun Xu ◽  
Na Wu ◽  
Yang Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Comparative Genomics ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Normal Diet ◽  
Specific Gene ◽  
Whole Genome ◽  
Metabolic Switch ◽  
M1 Macrophages ◽  
E Coli

ObjectiveThe gut microbiota is associated with nonalcoholic fatty liver disease (NAFLD). We isolated the Escherichia coli strain NF73-1 from the intestines of a NASH patient and then investigated its effect and underlying mechanism.Methods16S ribosomal RNA (16S rRNA) amplicon sequencing was used to detect bacterial profiles in healthy controls, NAFLD patients and NASH patients. Highly enriched E. coli strains were cultured and isolated from NASH patients. Whole-genome sequencing and comparative genomics were performed to investigate gene expression. Depending on the diet, male C57BL/6J mice were further grouped in normal diet (ND) and high-fat diet (HFD) groups. To avoid disturbing the bacterial microbiota, some of the ND and HFD mice were grouped as “bacteria-depleted” mice and treated with a cocktail of broad-spectrum antibiotic complex (ABX) from the 8th to 10th week. Then, E. coli NF73-1, the bacterial strain isolated from NASH patients, was administered transgastrically for 6 weeks to investigate its effect and mechanism in the pathogenic progression of NAFLD.ResultsThe relative abundance of Escherichia increased significantly in the mucosa of NAFLD patients, especially NASH patients. The results from whole-genome sequencing and comparative genomics showed a specific gene expression profile in E. coli strain NF73-1, which was isolated from the intestinal mucosa of NASH patients. E. coli NF73-1 accelerates NAFLD independently. Only in the HFD-NF73-1 and HFD-ABX-NF73-1 groups were EGFP-labeled E. coli NF73-1 detected in the liver and intestine. Subsequently, translocation of E. coli NF73-1 into the liver led to an increase in hepatic M1 macrophages via the TLR2/NLRP3 pathway. Hepatic M1 macrophages induced by E. coli NF73-1 activated mTOR-S6K1-SREBP-1/PPAR-α signaling, causing a metabolic switch from triglyceride oxidation toward triglyceride synthesis in NAFLD mice.ConclusionsE. coli NF73-1 is a critical trigger in the progression of NAFLD. E. coli NF73-1 might be a specific strain for NAFLD patients.

scholarly journals Draft Genome Sequences of Lactobacillus salivarius A3iob and Lactobacillus johnsonii CRL1647, Novel Potential Probiotic Strains for Honeybees (Apis mellifera L.)

2018 ◽  
Vol 7 (6) ◽  
Author(s):  
Marcela Carina Audisio ◽  
Leonardo Albarracín ◽  
Maria Julia Torres ◽  
Lucila Saavedra ◽  
Elvira Maria Hebert ◽  
...  
Keyword(s):  
Apis Mellifera ◽  
Genome Sequencing ◽  
Draft Genome ◽  
Illumina Miseq ◽  
Whole Genome ◽  
Genome Sequences ◽  
Lactobacillus Johnsonii ◽  
Lactobacillus Salivarius ◽  
Content Type ◽  
Probiotic Strains

This report describes the draft genome sequences of Lactobacillus salivarius A3iob and Lactobacillus johnsonii CRL1647, probiotic strains isolated from the gut of honeybee Apis mellifera workers. The reads were generated by a whole-genome sequencing (WGS) strategy on an Illumina MiSeq sequencer and were assembled into contigs with total sizes of 2,054,490 and 2,137,413 bp for the A3iob and CRL1647 strains, respectively.

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