Festival of Genomics 2024

I will be talking at the Festival of Genomics on Wednesday 24 January about Identifying virulence and antimicrobial resistance genes in bacterial using genome-wide association studies. You can preview my talk here.

View Global Distribution of Microbial AMR Genes with the New MicroBIGG-E Map

Graphical display provides new way to explore data! NCBI’s Pathogen Detection project provides the Microbial Browser for Identification of Genetic and Genomic Elements (MicroBIGG-E) which lets you browse anti-microbial resistance (AMR), stress response, virulence genes, and genomic elements found in genomes from the NCBI Isolates Browser.  We are excited to introduce the MicroBIGG-E Map, an … Continue reading View Global Distribution of Microbial AMR Genes with the New MicroBIGG-E Map

Full-scale access to microbial Pathogen Detection data in the Cloud!

NCBI’s Pathogen Detection resource now provides selected data on the Google Cloud Platform (GCP) allowing you better access to over 1 million bacterial isolates. Data on GCP include: The tables from the MicroBIGG-E database of anti-microbial resistance (AMR), stress response, virulence genes, and genomic elements and the Pathogen Isolates Browser that are both accessible through … Continue reading Full-scale access to microbial Pathogen Detection data in the Cloud!

Identifying resistance genes in tuberculosis

Newly published in PLOS Biology is our work identifying genes that confer resistance to common and last-resort antibiotics in bacteria that cause tuberculosis. Resistance to these drugs contributes to mortality and sickness on a pandemic scale every year, and disproportionately affects the poorest people in the world.

This new article is one of a series presenting results generated by more than 100 scientists across 23 countries across 5+ years as part of a collaboration called CRyPTIC.

Our role in CRyPTIC was the discovery of genes and mutations likely to cause drug resistance by applying a tool known as a genome-wide association study (GWAS), an approach we helped adapt to bacteria.

Using GWAS, we identified previously uncatalogued genes and mutations underlying resistance to every one of the 13 drugs we investigated. These include new and repurposed drugs, as well as the first- and second-line drugs more often used to treat tuberculosis.

Thanks to its generous funders, CRyPTIC dedicated scale (10,000+ genomes) and technical innovation (new high-throughput MIC assays) to help decode the DNA blueprint of antibiotic resistance. Pushing these boundaries has yielded a steep increase of up to 36% in the variation in resistance attributable to the genome for the important and previously understudied new and repurposed drugs.

Science at this scale can produce a seemingly overwhelming wealth of new information. We avoided the temptation to over-emphasize any individual result for the sake of simple narrative. Instead, we highlighted discoveries of uncatalogued genes or genetic variants that we found for every drug investigated:

The amidase AmiA2 and GTPase Era for bedaquiline.

The cytochrome P450 enzyme Cyp142 for clofazimine.

The serine/threonine protein kinase PknH for delaminid.

The antitoxin VapB20 for linezolid.

The PPE-motif family outer membrane protein PPE42 for amikacin and kanamycin.

The antibiotic-induced transcriptional regulator WhiB7 for ethionamide.

The rRNA methylase TlyA for levofloxacin.

The DNA gyrase subunit B GyrB for moxifloxacin.

The putative rhodaneses CysA2 and CysA3 for rifabutin.

The tRNA/rRNA methylase SpoU for ethambutol and rifampicin.

The multidrug efflux transport system repressor Rv1219 for isoniazid.

All these hits passed stringent evidence thresholds that take into account the large amount of data crunched. For each hit, we identified possible relationships between gene functions, such as they are known, and the mechanism of action of the antibiotics.

Beyond the biological discoveries of primary interest, this new paper unveils methodological advances in bacterial GWAS. We introduced a systematic, whole-genome approach to analysing not just short DNA sequences (so called oligonucleotide or “kmer”-based approaches), but also short sequences of the proteins that the DNA codes for (an oligopeptide-based approach). We have released our software on an open-source GitHub repository.

We also discovered a relationship that may help disentangle a technical issue in bacterial GWAS where the co-occurence of traits can trick us into thinking that a gene influences one trait when it influences another instead. For antimicrobial resistance, this issue is known as artefactual cross resistance. We observed that true associations tended to produce larger associations (as measured by the 'coefficient', rather than the p-value), providing a possible way to prioritize signals in the future.

This paper was published alongside the CRyPTIC Data Compendium in PLOS Biology, in which we released our data open source to the community, with resources provided by the European Bioinformatics Institute.

Some of the results of CRyPTIC have already been rushed into service by the World Health Organization on the grounds of exceptional importance based on a candidate gene approach; this includes the DNA gyrase subunit B – moxifloxacin association spotlighted above (Walker et al 2022). However, the new results go beyond a candidate gene approach, detecting a range of previously uncatalogued genes via its agnostic, whole-genome strategy.

Unpicking the genetics of antimicrobial resistance is a priority for improving rapid susceptibility tests for individual patients, selecting drug regimens that inhibit the evolution of multidrug resistance, and developing improved treatment options. The need is particularly great in M. tuberculosis, which killed 1.4 million people in 2019, owing to the slow (6-12 week) turnaround of traditional susceptibility testing, and the alarming threat of multidrug resistant tuberculosis. The discovery of many new candidate resistance variants therefore represents an advance that we hope will contribute to progress in reducing the burden of disease.

New paper: Antimicrobial resistance determinants are associated with Staphylococcus aureus bacteraemia and adaptation to the healthcare environment

Staphylococcus aureus is a leading cause of infectious disease deaths in all countries, with bloodstream infection leading to sepsis a major concern. This new study, published in November in Microbial Genomics, reports genes and genetic variants in Staph. aureus associated severe disease vs asymptomatic carriage, and healthcare vs community carriage.

Our genome-wide association study of 2000 bacterial genomes showed that antibiotic resistance in Staph. aureus is associated with severe disease and the hospital environment:

  • A mutation conferring trimethoprim resistance (dfrB F99Y) and the presence of a gene conferring methicillin resistance (mecA) were both associated with bloodstream infection vs asymptomatic nose carriage.
  • Separately, we demonstrated that a mutation conferring fluoroquinolone resistance (gyrA L84S) and variation in a gene involved in resistance to multiple antibiotics (prsA) were preferentially associated with healthcare-associated carriage vs community-acquired carriage.

The implication – that antibiotic resistance genes may provide survival advantages which mechanistically contribute to the development of disease – is important in the face of the continued global rise of antibiotic resistance.


We were also able to shed light on a controversy as to whether different strains of Staph. aureus differ in their propensity to cause severe disease. Interest in this question dates back decades in the literature, and contradictory studies, often based on modest sample sizes, have reached different conclusions. Our comparatively large study, using a whole-genome method that we previously published in Nature Microbiology, found that all strains of Staph. aureus are equally likely to cause severe disease vs asymptomatic carriage.




New paper: GenomegaMap for dN/dS in over 10,000 genomes

Published this week in Molecular Biology and Evolution, is a new paper joint with the CRyPTIC Consortium "GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes".

The dN/dS ratio is a popular statistic in evolutionary genetics that quantifies the relative rates of protein-altering and non-protein-altering mutations. The rate is adjusted so that under neutral evolution - i.e. when the survival and reproductive advantage of all variants is the same - it equals 1. Typically, dN/dS is observed to be less than 1 meaning that new mutations tend to be disfavoured, implying they are harmful to survival or reproduction. Occasionally, dN/dS is observed to be greater than 1 meaning that new mutations are favoured, implying they provide some survival or reproductive advantage. The aim of estimating dN/dS is usually to identify mutations that provide an advantage.

Theoreticians are often critical of dN/dS because it is more of a descriptive statistic than a process-driven model of evolution. This overlooks the problem that currently available models make simplifying assumptions such as minimal interference between adjacent mutations within genes. These assumptions are not obviously appropriate in many species, including infectious micro-organisms, that exchange genetic material infrequently.

There are many methods for measuring dN/dS. This new paper overcomes two common problems:
  • It is fast no matter how many genomes are analysed together.
  • It is robust whether there is frequent genetic exchange (which causes phylogenetic methods to report spurious signals of advantageous mutation) or infrequent genetic exchange.
The paper includes detailed simulations that establish the validity of the approach, and it goes on to demonstrate how genomegaMap can detect advantageous mutations in 10,209 genomes of Mycobacterium tuberculosis, the bacterium that causes tuberculosis. The method reproduces known signals of advantageous mutations that make the bacteria resistant to antibiotics, and it discovers a new signal of advantageous mutations in a cold-shock protein called deaD or csdA.

Software that implements genomegaMap is available on Docker Hub and the source code and documentation are available on Git Hub.

With the steady rise of more and more genome sequences, the analysis of data becomes an increasing challenge even with modern computers, so it is hoped that this new method provides a useful way to exploit the opportunities in such large datasets to gain new insights into evolution.

New publication on AMRFinder, a tool that identifies resistance genes in pathogen genomes!

Read the recent publication (PMID: 31427293) on the AMRFinder, a tool that identifies antimicrobial resistance (AMR) genes in bacterial genome sequences using a high-quality curated AMR gene reference database.  We use the AMRFinder to identify AMR genes in the hundreds of bacterial … Continue reading

Are antibiotics making printers great…again?

Are antibiotics making printers great...again? | www.APHLblog.org

By Eric Ransom, APHL-CDC Antimicrobial Resistance Fellow

Let’s be honest: printers have never been that great. These frustrating devices turn what should be a simple office task into a game of chance. Is there paper? Did it jam? Can I get by without replacing the toner cartridge… again? Ugh! I personally cannot wait until this archaic technology sails off into the sunset. Goodbye frustration and hello forestation.

You can imagine my surprise when I heard a PRINTER could help fight one of the most significant public health threats of our time: antibiotic resistance. That’s right. The end of the antibiotic era looms, but hope lies with a printer!

To be fair, this is not your ordinary printer that puts ink to paper. This is a bioprinter that “prints” antibiotics! The technology ultimately helps clinicians decide which antibiotic is most likely to be effective in treating an infection. Prescribing the proper antibiotic is key to saving lives today and preserving antibiotics for tomorrow.

More specifically, the bioprinter makes antibiotic panels for broth microdilution susceptibility testing, a gold-standard method in clinical and public health microbiology. To make an antibiotic panel, the bioprinter dispenses minuscule amounts of antibiotics into a 96-well plate containing liquid that supports microbial growth. Microbiologists can then add a patient’s microbe to the plate and observe which antibiotic (or combination of antibiotics) inhibits growth. If an antibiotic inhibits growth on the plate, chances are good that it will also inhibit growth in the person. Results are shared with clinicians so they can prescribe the best antibiotic(s) to treat the infection. What makes the bioprinter unique is that it can easily make antibiotic plates with complex antibiotic combinations and new-to-market antibiotics. The latter is especially exciting given it can take years before new-to-market antibiotics are included on commercially available plates and systems found in most hospital laboratories.

In 2018, the Centers for Disease Control and Prevention announced a pilot program to implement the bioprinter technology in the Antibiotic Resistance Laboratory Network, a consortium of 56 public health laboratories that aims to rapidly detect and respond to antibiotic resistance. The pilot program already uses the bioprinter to offer expanded antibiotic susceptibility testing for hard-to-treat infections in four public health laboratories: Wisconsin State Laboratory of Hygiene, Minnesota Department of Health Public Health Laboratory, Wadsworth Center Laboratories and Tennessee State Public Health Laboratory. This susceptibility testing is free, compliant with patient testing regulations, and available for all qualifying isolates from any hospital laboratory. The testing is also performed within three working days to quickly assist clinicians with therapeutic management.

The pilot program has already begun susceptibility testing with a new drug combination (aztreonam-avibactam) against Enterobacteriaceae producing a metallo-β-lactamase (MβL). These are some of the most resistant microbes, and there are very few effective treatment options. To qualify for this particular testing, isolates must be non-susceptible to all current β-lactam antibiotics (including either ceftazidime-avibactam or meropenem-vaborbactam). Moving forward, the pilot program will expand testing to include other highly resistant microbes and new-to-market antibiotics.

So how exactly does the bioprinter pilot program work in practice? Let’s say a hospital patient has symptoms of a serious infection. Samples from the patient are tested in the hospital’s laboratory to identify the responsible microbe and to determine possible treatment options. If the microbe is found to be highly resistant and clinicians are in need of additional treatment options, the microbe is sent to one of the four public health laboratories piloting the bioprinter program. Microbiologists there can use the bioprinter to print plates for testing the newest antibiotics to see what, if any, are effective in treating the patient’s infection. Results are then returned to clinicians where the patient is being treated.

Implementation of the bioprinter in the AR Lab Network has the potential to be truly impactful. First, clinicians are given a resource to find new, effective treatment options for their patients’ most resistant infections. Second, compiled data from this pilot program can be used to improve antibiotic prescribing, capture national antibiotic efficacy, help establish antibiotic breakpoints and even inform infection control and prevention practices.

The bioprinter pilot program is a remarkable step forward in the fight against antibiotic resistance. It is important to realize though that this crisis still requires comprehensive long-term intervention including discovery of new antibiotics, development of new diagnostics, and an unequivocal commitment to antibiotic stewardship in healthcare and beyond. In the short term, though, a printer might just be exactly what the doctor ordered.

The post Are antibiotics making printers great…again? appeared first on APHL Lab Blog.

Improved search makes it easier to find antimicrobial resistance protein information

It’s now easier to find known antimicrobial resistance (AMR) protein information at NCBI. You can search by gene symbol, protein name, or accession across NCBI databases and retrieve the best representative DNA sequence that is a reference for antimicrobial resistance … Continue reading