Why NGS is the next big step in the AMR battle
Since their discovery, antimicrobials have revolutionised the treatment of infectious diseases. Their availability allows the existence of life saving interventions like surgeries, intensive care and organ transplants. Not only for humans, they are widely used in treatment of animals, from pets to livestock to fisheries, and even in the food industry.
In less than 100 years though, over-dependence and prolonged use of antimicrobials have exerted enormous selective pressure on microbial populations, dramatically accelerating the evolution of antimicrobial resistance (AMR). Genes conferring such a resistant phenotype can be naturally present in the species population or be horizontally acquired (HGT) via mobile genetic elements, like plasmids carrying the resistance genes. Thus, as soon as a new class of small molecule is introduced to kill these microbes, organisms evolve to resist their action leading to increased resistance.
Scope of the problem
The spread of AMR is a complex phenomenon driven by multiple factors like unprescribed consumption of broad spectrum antibiotics, inadequate infection control measures, high prevalence of infectious diseases, poor public health system and the widespread dissemination of resistant pathogens through travel. Studies on AMR disproportionately focus on humans while comprehensive data on antimicrobial use in sectors like agriculture, animal husbandry, livestock, veterinary, fisheries and food products remain lacking. However, evidence suggests that areas like wastewater and contaminated soil accumulate antimicrobial residues becoming environmental hubs for the rise of AMR[1].
Rising AMR not only increases hospitalizations and deaths, but also puts immense pressure on health care systems and economies. In 2019 alone, worldwide, 2.27 million deaths were attributed to AMR, while the financial burden of AMR in the US alone was estimated to be close to $55 billion per year[2]. These numbers are likely to look way larger for low- and middle- income countries that carry the largest burden of AMR, threatening sustainable development in these parts of the world.
While developing new antimicrobials and vaccines is part of the solution, a multipronged problem like AMR that intertwines human health, animal welfare and environmental dynamics demands a holistic and sustainable “One Health” approach[3]. Modern Next Generation Sequencing technologies (NGS) make community surveillance, tracing and diagnosis cheaper and easier, providing accurate and timely estimates of the AMR burden, informing policies and treatment guidelines.
Next Gen Sequencing as a tool to understand AMR
Genomes contain information about drug resistance, standing mutations and clonal lineage of different isolates. Current NGS technologies not only provide accurate and rapid identification of pathogens and their related AMR genes but also sheds light on transmission pathways between environmental AMR hubs like hospitals and community settings, boosting the capacity to effectively monitor and target outbreaks in a timely fashion[4].
Compared to the traditional phenotype and metabolism based AMR detection methods that depend on the ability to culture microbes in lab conditions and require high abundance, NGS methods are often unbiased, pathogen agnostic and allow sensitive culture-free direct from patients diagnostics.
Compared to the traditional phenotype and metabolism based AMR detection methods that depend on the ability to culture microbes in lab conditions and require high abundance, NGS methods are often unbiased, pathogen agnostic and allow sensitive culture-free direct from patients diagnostics. These methods provide more exhaustive profiling of AMR features allowing discovery of completely new resistance patterns and novel plasmids detecting changes in taxonomic composition and functional genes[5], [6].
Amplicon sequencing
NGS allows patient or environmental samples to be used directly with minimum pre-processing. Targeted sequencing, also known as amplicon sequencing, enriches for specific sequences of interest and is widely used for fast (results are obtained in hours compared to days) and accurate diagnostics in hospitals and laboratories. For example, 16S rRNA and hypervariable regions are routinely used for identifying individual species as well as characterising complex microbial communities, tracking and comparing diversity of complex environments from metagenomic samples. Commercially available syndromic panels allow testing for multiple pathogens and genes at a time. These kits are available for a plethora of infectious diseases like respiratory, blood, urinary tract infection and viral profiling. The biggest drawbacks of amplicon sequencing is that it is hypothesis (primer) driven and can detect only a subset of genes and pathogens.
Whole genome sequencing and Metagenomics
Shotgun sequencing and Whole genome sequencing (WGS) are sequence agnostic and hypothesis (primer) free NGS methods used for whole genome and metagenome sequencing. Unlike shotgun sequencing that can be done on direct samples, WGS uses second (Illumina) or third generation (Nanopore, PacBio) technologies that are useful for purified colonies. These methods are used to get accurate taxonomic and functional profiling with improved genus and species level information. These methods are especially useful in detection of fastidious organisms such as Mycobacterium and Neisseria, and in cases where species level identification is imperative due to differences in antibiotic susceptibility between species, such as in the case of Salmonella where serotyping is absolutely essential.
Shotgun sequencing and WGS has found its application in studying the resistomes of human and animal microbiomes, different habitats like agriculture and urban soils, and local and international AMR surveillance of specific strains. In the recent past this technology has been used for meticulous local and international genomic surveillance allowing timely actions to limit bacterial outbreaks like those of multi-resistance Staphylococcus aureus, Mycobacterium tuberculosis and Enterobacterales. As a matter of fact, RNA based metagenomic sequencing of respiratory samples from multiple patients in Wuhan is what allowed researchers to identify the cause of COVID-19 outbreak[7]. Another NGS based study on nasal cavity colonisation patterns in neonates found that hospital associated strains spread not only via contact but are also transmitted by air particles via AC vents[8].
Using such metagenomic approaches Mahnert et al (2019) showed that more confined and cleaned environments have reduced microbial diversity and increased resistance suggesting the need for strategies to restore bacterial diversity in certain built environments. Genomic analysis of hospital waste water across 23 different countries demonstrated higher amounts of AMR genes, highlighting hospital effluent as a source of AMR spread in the environment. Another systematic investigation revealed the changes in hospital microbiota based on the sanitation scheme adopted by the hospital. These examples not only highlight the need for hospitals to re-think sanitation approaches in order to limit AMR spread, but also the importance of active environmental monitoring in AMR hubs like hospitals[5].
WGS has also helped identify new antibiotic resistant genes (ARGs) and population dynamics.
WGS has also helped identify new antibiotic resistant genes (ARGs) and population dynamics. For example, a study conducted by Haystack analytics and IIT-Bombay assessing the reliability and applicability of WGS in public health care settings found implementing WGS for tuberculosis reduced turn-around times from up to 3 weeks to as low as 1 week[9]. Another study exploring metagenomes of gut microbes from pre-school children found an enrichment of large viral genomes and bacteriophages of many human pathogens along with previously reported plasmid associated ARGs. The significance of such microbial community composition and interactions in maintaining AMR loads is poorly understood[10].
WGS and shotgun sequencing technologies have also been capitalised for diagnosis of infectious pathogens. Companies like Haystack analytics use Nanopore technology for early detection of sepsis in hospital settings along with kits that allow detection of more than 200 pathogens. Similarly IDbyDNA and ARUP lab changed the diagnostic landscape of respiratory diseases using shotgun sequencing as early as 2017.
One major drawback of NGS is the genotype to phenotype mapping. Simply because a microbe carries a resistant gene does not necessarily mean that it also expresses it. Thus, NGS based diagnostics may overcall resistance. These tests also cannot detect non-enzymatic resistance mechanisms like loss of porins or upregulation of efflux pumps. However, availability of unbiased genomic and transcriptomic data driven detection of microorganisms on single platforms like Nanopore coupled with patient history, disease progression and geography is now being used to develop diagnostic machine learning algorithms that can accurately predict new mutations as well as the drug-microbe combinations aiding clinical decisions, optimal diagnostics, therapy, better patient outcomes and shorter hospital stays[11].
Combating Antibiotic-Resistant Bacteria Biopharmaceutical Accelerator (CARB-X) is a global non-profit partnership accelerating innovations by supporting development of new antibacterial products to address drug-resistant bacteria. CARB-X and CCAMP support companies like Clemedi, and Genome-Key that use NGS combined with AI/ML tools to develop diagnostics for infectious diseases with the aim to shorten reporting times from days to hours.
Conclusion
NGS represents huge leaps in our capabilities to understand the host-pathogen-environment interaction. In the future, one can expect incorporation of proteomics workflow with NGS pipelines to get better phenotypic profiles. Combined with good field data, centralised databases and prediction algorithms NGS can overcome many confounding cases and play a part not only in improving and cheaper diagnostics but also informing public policy choices dictating AMR control.
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