Resistome

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The resistome has been used to describe to two similar yet separate concepts:

Contents

Discovery and Current Data

The resistome was first used to describe the resistance capabilities of bacteria preventing the effectiveness of antibiotics . [4] [5] Although antibiotics and their accompanying antibiotic resistant genes come from natural habitats, before next-generation sequencing, most studies of antibiotic resistance had been confined to the laboratory. [6] Increased availability of whole-genome and metagenomic next-generation sequencing techniques have revealed significant reservoirs of antibiotic resistant bacteria outside of clinical settings. [4] [7] [8] [9] Repeated testing of soil metagenomes revealed that in urban, agricultural, and forest environments, spore-forming soil bacteria showed resistance to most major antibiotics regardless of where they'd originated. [4] In this study, they observed nearly 200 different resistance profiles among the bacteria sequenced, indicating a diverse and robust response to the antibiotics tested regardless of their bacterial target or natural or synthetic origin. [4] Antibiotic resistant bacteria have observed through metagenomic surveys in non-clinical environments such as water treatment facilities [5] [8] and human microbiomes like the mouth. [10] We now know that the antibiotic resistome exists in every environmental niche on Earth, and sequences from ancient permafrost reveal that antibiotic resistance has been around millennia before the introduction of human-synthesized antibiotics. [9]

The Comprehensive Antibiotic Research Database (CARD) was created to compile a database of resistance genes from this rapidly increasingly available bacterial genomic data. [7] The CARD is a compilation of sequence data and identification of resistance genes in unannotated genome sequences. [7] The database "includes bioinformatic tools that enable the identification of antibiotic resistance genes from whole- or partial-genome sequence data, including unannotated raw sequence assembly contigs”. [7] It is a resource intended to create a better understanding of the resistome and links healthcare, environmental, agricultural datasets. [7]

The ResistomeDB was published in 2020 to store the Global Ocean Resistome [11] ., based on the metagenomics samples from the Tara Oceans Project.

Human pathogens

A major question surrounding the environmental resistome is: How do pathogenic bacteria acquire antibiotic resistance genes from the environment (and vice versa)? To answer this, we need to consider the mechanisms of horizontal gene transfer (HGT) and the various opportunities for contact between environmental bacteria and human pathogens. [ citation needed ]

In soil antibiotic resistant bacterial communities, resistance-conferring genes have been found on mobile genetic elements. [4] Similarly, in an analysis of the resistome in a water treatment plant, plasmids and other protein-coding mobile genetic elements were present at all levels of filtration, and these mobile elements harbored genes for resistance. [5] These soil and water-based resistant communities are known as reservoirs, from which resistance can transfer to pathogenic bacteria. [12] Metagenomic sequencing and short-read based assembly have revealed the exchange of antibiotic resistance genes between non-pathogenic environmental soil bacteria and clinical pathogens. [13] The portions in the soil bacteria perfectly match the identity of several diverse human pathogens and contain resistance cassettes against five classes of antibiotics. [13] These resistance cassettes also contain sequences that reflect recent horizontal gene transfer and provide the mechanism for how that transfer occurred. [13] These antibiotic resistant genes also retain their functionality even after they are entirely removed from the context of their original host, emphasizing their compatibility with a wide range of hosts, including pathogens. [13] Interestingly, the high conservation of resistance gene identity also was observed in the human gut microbiome. [13] Although the average amino acid similarity between human gut microbiota and resistant pathogens was only around 30.2 to 45.5%, their resistance genes perfectly matched those of the pathogenic bacteria, suggesting the resistomes of the human gastrointestinal tract, soil, and clinical pathogens are all connected. [13] It should be noted, however, that the risk of transmission cannot simply be extrapolated from abundance of resistome genes in a population, and a multifaceted approach to risk analyses should be considered to fully understand the risks posed. [12] For example, the mobility of antibiotic resistant genes has been observed to be dependent on if the population is pathogenic or not, with pathogen communities having far higher proportions of mobile genetic elements. [14]

When antibiotic resistance is present in the environment, it is important to consider how human pathogens are interacting or integrated into those environments, and how antibiotic resistance is being exchanged there. For example, mouth bacteria can reach other parts of the body through the digestive and blood systems, and our saliva readily transfers bacteria to other people, so there are several ways for antibiotic resistant bacteria in the oral micriobiome to readily transfer their resistance genes to other, potentially pathogenic bacterial communities. [10] Additionally, soil and pathogenic resistomes have been observed not to be distinct, so it’s essential that we understand environmental resistance in aquatic and other environments with high likelihood of human pathogen interaction. [13] In the hyper-antibiotic resistant Pseudomonas aeruginosa environmental stress key to the way its resistome is expressed; intrinsic, acquired, and adaptive forms of resistant gene expression occur under different environmental pressures and lead to significant challenges in developing effective treatments in response. [15]

Our understanding of how humans create additional positive selective pressure for antibiotic resistance in non-clinical environments is essential now more than ever. [4] [5] The rise in antibiotic resistance has severely reduced the efficacy of antibiotic drugs, posing severe cause for concern in the realm of drug development and maintaining public health. [9] Human-manufactured antibiotics are not the only source of antibiotic resistant pressure in the wild, as antibiotics are present at various concentrations and function as both defense and signaling mechanisms, selecting for antibiotic resistance naturally in the environment. [6] For this reason, studying natural antibiotics and the patterns of antibiotic resistance that naturally arise in the wild may help us to predict and respond to antibiotic resistance in clinical settings. [6] Analyses of metagenomic sequence data are useful tools for understanding how human impact influences the spread of resistance genes. [13] An effect of the introduction of high levels of human-made antibiotics in the environment is the promotion of antibiotic resistance even in the absence of natural antibiotic production. [4] Secondary stress conditions like heavy metal pollution cause higher HGT as a stress response, which also likely contributes to the dissemination of antibiotic resistant genes. [6] Also, rapid increase in human populations without adequate wastewater treatment allows for more chance for human pathogens to be in contact with environmental resistance-carrying bacteria, [6] so it's important to look to wastewater treatment as a source of HGT. [10]

Infection resistance

The resistome also refers to an inherited set of genes used to resist infections. [3] [2] This concept is also referred to as innate immunity, and resistance genes within the resistome provide different functions for immune response, and are differentially transcribed. [3] Interestingly, in one study of Arabidopsis thaliana, activated regions on  the chromosome for resistance against both bacteria and viruses are clustered together, likely meaning they are co-regulated. [3]

Comparing different mutations in the germline can be used to help define the size and position of the resistome, this set of genes conferring an inherited immune response. [2] Because of mutation, the ‘universal resistome’, a set of resistance genes shared among all mice, similar to the concept of the pan-microbiome, [16] is likely extremely small. [2]

Related Research Articles

<span class="mw-page-title-main">Antimicrobial resistance</span> Resistance of microbes to drugs directed against them

Antimicrobial resistance (AMR) occurs when microbes evolve mechanisms that protect them from the effects of antimicrobials. All classes of microbes can evolve resistance where the drugs are no longer effective. Fungi evolve antifungal resistance. Viruses evolve antiviral resistance. Protozoa evolve antiprotozoal resistance, and bacteria evolve antibiotic resistance. Together all of these come under the umbrella of antimicrobial resistance. Microbes resistant to multiple antimicrobials are called multidrug resistant (MDR) and are sometimes referred to as a superbugs. Although antimicrobial resistance is a naturally occurring process, it is often the result of improper usage of the drugs and management of the infections.

<span class="mw-page-title-main">Bacteriophage</span> Virus that infects and replicates within bacteria

A bacteriophage, also known informally as a phage, is a virus that infects and replicates within bacteria and archaea. The term was derived from "bacteria" and the Greek φαγεῖν, meaning "to devour". Bacteriophages are composed of proteins that encapsulate a DNA or RNA genome, and may have structures that are either simple or elaborate. Their genomes may encode as few as four genes and as many as hundreds of genes. Phages replicate within the bacterium following the injection of their genome into its cytoplasm.

<span class="mw-page-title-main">Biofilm</span> Aggregation of bacteria or cells on a surface

A biofilm comprises any syntrophic consortium of microorganisms in which cells stick to each other and often also to a surface. These adherent cells become embedded within a slimy extracellular matrix that is composed of extracellular polymeric substances (EPSs). The cells within the biofilm produce the EPS components, which are typically a polymeric conglomeration of extracellular polysaccharides, proteins, lipids and DNA. Because they have three-dimensional structure and represent a community lifestyle for microorganisms, they have been metaphorically described as "cities for microbes".

<span class="mw-page-title-main">Human microbiome</span> Microorganisms in or on human skin and biofluids

The human microbiome is the aggregate of all microbiota that reside on or within human tissues and biofluids along with the corresponding anatomical sites in which they reside, including the skin, mammary glands, seminal fluid, uterus, ovarian follicles, lung, saliva, oral mucosa, conjunctiva, biliary tract, and gastrointestinal tract. Types of human microbiota include bacteria, archaea, fungi, protists, and viruses. Though micro-animals can also live on the human body, they are typically excluded from this definition. In the context of genomics, the term human microbiome is sometimes used to refer to the collective genomes of resident microorganisms; however, the term human metagenome has the same meaning.

<span class="mw-page-title-main">Horizontal gene transfer</span> Type of nonhereditary genetic change

Horizontal gene transfer (HGT) or lateral gene transfer (LGT) is the movement of genetic material between organisms other than by the ("vertical") transmission of DNA from parent to offspring (reproduction). HGT is an important factor in the evolution of many organisms. HGT is influencing scientific understanding of higher order evolution while more significantly shifting perspectives on bacterial evolution.

<i>Acinetobacter</i> Genus of bacteria

Acinetobacter is a genus of Gram-negative bacteria belonging to the wider class of Gammaproteobacteria. Acinetobacter species are oxidase-negative, exhibit twitching motility, and occur in pairs under magnification.

<span class="mw-page-title-main">Metagenomics</span> Study of genes found in the environment

Metagenomics is the study of genetic material recovered directly from environmental or clinical samples by a method called sequencing. The broad field may also be referred to as environmental genomics, ecogenomics, community genomics or microbiomics.

<i>Bacteroides</i> Genus of bacteria

Bacteroides is a genus of Gram-negative, obligate anaerobic bacteria. Bacteroides species are non endospore-forming bacilli, and may be either motile or nonmotile, depending on the species. The DNA base composition is 40–48% GC. Unusual in bacterial organisms, Bacteroides membranes contain sphingolipids. They also contain meso-diaminopimelic acid in their peptidoglycan layer.

In biology, a gene cassette is a type of mobile genetic element that contains a gene and a recombination site. Each cassette usually contains a single gene and tends to be very small; on the order of 500–1000 base pairs. They may exist incorporated into an integron or freely as circular DNA. Gene cassettes can move around within an organism's genome or be transferred to another organism in the environment via horizontal gene transfer. These cassettes often carry antibiotic resistance genes. An example would be the kanMX cassette which confers kanamycin resistance upon bacteria.

<i>Acinetobacter baumannii</i> Species of bacterium

Acinetobacter baumannii is a typically short, almost round, rod-shaped (coccobacillus) Gram-negative bacterium. It is named after the bacteriologist Paul Baumann. It can be an opportunistic pathogen in humans, affecting people with compromised immune systems, and is becoming increasingly important as a hospital-derived (nosocomial) infection. While other species of the genus Acinetobacter are often found in soil samples, it is almost exclusively isolated from hospital environments. Although occasionally it has been found in environmental soil and water samples, its natural habitat is still not known.

<span class="mw-page-title-main">Microbiota</span> Community of microorganisms

Microbiota are the range of microorganisms that may be commensal, mutualistic, or pathogenic found in and on all multicellular organisms, including plants. Microbiota include bacteria, archaea, protists, fungi, and viruses, and have been found to be crucial for immunologic, hormonal, and metabolic homeostasis of their host.

Pathogenomics is a field which uses high-throughput screening technology and bioinformatics to study encoded microbe resistance, as well as virulence factors (VFs), which enable a microorganism to infect a host and possibly cause disease. This includes studying genomes of pathogens which cannot be cultured outside of a host. In the past, researchers and medical professionals found it difficult to study and understand pathogenic traits of infectious organisms. With newer technology, pathogen genomes can be identified and sequenced in a much shorter time and at a lower cost, thus improving the ability to diagnose, treat, and even predict and prevent pathogenic infections and disease. It has also allowed researchers to better understand genome evolution events - gene loss, gain, duplication, rearrangement - and how those events impact pathogen resistance and ability to cause disease. This influx of information has created a need for bioinformatics tools and databases to analyze and make the vast amounts of data accessible to researchers, and it has raised ethical questions about the wisdom of reconstructing previously extinct and deadly pathogens in order to better understand virulence.

In biology, a pathogen, in the oldest and broadest sense, is any organism or agent that can produce disease. A pathogen may also be referred to as an infectious agent, or simply a germ.

<span class="mw-page-title-main">Lactocillin</span> Chemical compound

Lactocillin is a thiopeptide antibiotic which is encoded for and produced by biosynthetic genes clusters in the bacteria Lactobacillus gasseri. Lactocillin was discovered and purified in 2014. Lactobacillus gasseri is one of the four Lactobacillus bacteria found to be most common in the human vaginal microbiome. Due to increasing levels of pathogenic resistance to known antibiotics, novel antibiotics are increasingly valuable. Lactocillin could function as a new antibiotic that could help people fight off infections that are resistant to many other antibiotics.

<span class="mw-page-title-main">Pharmacomicrobiomics</span>

Pharmacomicrobiomics, proposed by Prof. Marco Candela for the ERC-2009-StG project call, and publicly coined for the first time in 2010 by Rizkallah et al., is defined as the effect of microbiome variations on drug disposition, action, and toxicity. Pharmacomicrobiomics is concerned with the interaction between xenobiotics, or foreign compounds, and the gut microbiome. It is estimated that over 100 trillion prokaryotes representing more than 1000 species reside in the gut. Within the gut, microbes help modulate developmental, immunological and nutrition host functions. The aggregate genome of microbes extends the metabolic capabilities of humans, allowing them to capture nutrients from diverse sources. Namely, through the secretion of enzymes that assist in the metabolism of chemicals foreign to the body, modification of liver and intestinal enzymes, and modulation of the expression of human metabolic genes, microbes can significantly impact the ingestion of xenobiotics.

ESKAPE is an acronym comprising the scientific names of six highly virulent and antibiotic resistant bacterial pathogens including: Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. The acronym is sometimes extended to ESKAPEE to include Escherichia coli. This group of Gram-positive and Gram-negative bacteria can evade or 'escape' commonly used antibiotics due to their increasing multi-drug resistance (MDR). As a result, throughout the world, they are the major cause of life-threatening nosocomial or hospital-acquired infections in immunocompromised and critically ill patients who are most at risk. P. aeruginosa and S. aureus are some of the most ubiquitous pathogens in biofilms found in healthcare. P. aeruginosa is a Gram-negative, rod-shaped bacterium, commonly found in the gut flora, soil, and water that can be spread directly or indirectly to patients in healthcare settings. The pathogen can also be spread in other locations through contamination, including surfaces, equipment, and hands. The opportunistic pathogen can cause hospitalized patients to have infections in the lungs, blood, urinary tract, and in other body regions after surgery. S. aureus is a Gram-positive, cocci-shaped bacterium, residing in the environment and on the skin and nose of many healthy individuals. The bacterium can cause skin and bone infections, pneumonia, and other types of potentially serious infections if it enters the body. S. aureus has also gained resistance to many antibiotic treatments, making healing difficult. Because of natural and unnatural selective pressures and factors, antibiotic resistance in bacteria usually emerges through genetic mutation or acquires antibiotic-resistant genes (ARGs) through horizontal gene transfer - a genetic exchange process by which antibiotic resistance can spread.

<span class="mw-page-title-main">Malacidin</span> Chemical compound

Malacidins are a class of chemicals made by bacteria found in soil that can kill Gram-positive bacteria. Their activity appears to be dependent on calcium. The discovery of malacidins was published in 2018.

FARME also known as Functional Antibiotic Resistance Metagenomic Element is a database that compiles publicly available DNA elements and predicted proteins that confer antibiotic resistance, regulatory elements and mobile genetic elements. It is the first database to focus on functional metagenomics. This allows the database to understand 99% of bacteria which cannot be cultured, the relationship between environmental antibiotic resistance sequences and antibiotic genes derived from cultured isolates. This information was derived from 20 metagenomics projects from GenBank. Also from GenBank are the protein sequence predictions and annotations.

Clinical metagenomic next-generation sequencing (mNGS) is the comprehensive analysis of microbial and host genetic material in clinical samples from patients by next-generation sequencing. It uses the techniques of metagenomics to identify and characterize the genome of bacteria, fungi, parasites, and viruses without the need for a prior knowledge of a specific pathogen directly from clinical specimens. The capacity to detect all the potential pathogens in a sample makes metagenomic next generation sequencing a potent tool in the diagnosis of infectious disease especially when other more directed assays, such as PCR, fail. Its limitations include clinical utility, laboratory validity, sense and sensitivity, cost and regulatory considerations.

References

  1. Wright, Gerard D. (March 2007). "The antibiotic resistome: the nexus of chemical and genetic diversity". Nature Reviews Microbiology. 5 (3): 175–186. doi: 10.1038/nrmicro1614 . ISSN   1740-1526. PMID   17277795. S2CID   6820908.
  2. 1 2 3 4 Beutler B, Crozat K, Koziol JA, Georgel P (February 2005). "Genetic dissection of innate immunity to infection: the mouse cytomegalovirus model". Current Opinion in Immunology. 17 (1): 36–43. doi:10.1016/j.coi.2004.11.004. PMID   15653308.
  3. 1 2 3 4 Marathe R, Guan Z, Anandalakshmi R, Zhao H, Dinesh-Kumar SP (July 2004). "Study of Arabidopsis thaliana resistome in response to cucumber mosaic virus infection using whole genome microarray". Plant Molecular Biology. 55 (4): 501–20. doi:10.1007/s11103-004-0439-0. PMID   15604696. S2CID   7460917.
  4. 1 2 3 4 5 6 7 D'Costa VM, McGrann KM, Hughes DW, Wright GD (January 2006). "Sampling the antibiotic resistome". Science. 311 (5759): 374–7. Bibcode:2006Sci...311..374D. doi:10.1126/science.1120800. PMID   16424339. S2CID   14411188.
  5. 1 2 3 4 Dias MF, da Rocha Fernandes G, Cristina de Paiva M, Christina de Matos Salim A, Santos AB, Amaral Nascimento AM (May 2020). "Exploring the resistome, virulome and microbiome of drinking water in environmental and clinical settings". Water Research. 174: 115630. Bibcode:2020WatRe.17415630D. doi:10.1016/j.watres.2020.115630. PMID   32105997. S2CID   211556937.
  6. 1 2 3 4 5 Martínez JL (July 2008). "Antibiotics and antibiotic resistance genes in natural environments". Science. 321 (5887): 365–7. Bibcode:2008Sci...321..365M. doi:10.1126/science.1159483. PMID   18635792. S2CID   38529155.
  7. 1 2 3 4 5 McArthur AG, Waglechner N, Nizam F, Yan A, Azad MA, Baylay AJ, et al. (July 2013). "The comprehensive antibiotic resistance database". Antimicrobial Agents and Chemotherapy. 57 (7): 3348–57. doi:10.1128/AAC.00419-13. PMC   3697360 . PMID   23650175.
  8. 1 2 Manaia CM, Rocha J, Scaccia N, Marano R, Radu E, Biancullo F, et al. (June 2018). "Antibiotic resistance in wastewater treatment plants: Tackling the black box". Environment International. 115: 312–324. doi:10.1016/j.envint.2018.03.044. PMID   29626693. S2CID   4686577.
  9. 1 2 3 Brown ED, Wright GD (January 2016). "Antibacterial drug discovery in the resistance era". Nature. 529 (7586): 336–43. Bibcode:2016Natur.529..336B. doi:10.1038/nature17042. PMID   26791724. S2CID   4401156.
  10. 1 2 3 Diaz-Torres ML, Villedieu A, Hunt N, McNab R, Spratt DA, Allan E, et al. (May 2006). "Determining the antibiotic resistance potential of the indigenous oral microbiota of humans using a metagenomic approach". FEMS Microbiology Letters. 258 (2): 257–62. doi: 10.1111/j.1574-6968.2006.00221.x . PMID   16640582.
  11. Cuadrat, Rafael R C; Sorokina, Maria; Andrade, Bruno G; Goris, Tobias; Dávila, Alberto M R (2020-05-01). "Global ocean resistome revealed: Exploring antibiotic resistance gene abundance and distribution in TARA Oceans samples". GigaScience. 9 (5). doi:10.1093/gigascience/giaa046. ISSN   2047-217X. PMC   7213576 . PMID   32391909.
  12. 1 2 Manaia CM (March 2017). "Assessing the Risk of Antibiotic Resistance Transmission from the Environment to Humans: Non-Direct Proportionality between Abundance and Risk". Trends in Microbiology. 25 (3): 173–181. doi: 10.1016/j.tim.2016.11.014 . PMID   28012687.
  13. 1 2 3 4 5 6 7 8 Forsberg KJ, Reyes A, Wang B, Selleck EM, Sommer MO, Dantas G (August 2012). "The shared antibiotic resistome of soil bacteria and human pathogens". Science. 337 (6098): 1107–11. Bibcode:2012Sci...337.1107F. doi:10.1126/science.1220761. PMC   4070369 . PMID   22936781.
  14. Forsberg KJ, Patel S, Gibson MK, Lauber CL, Knight R, Fierer N, Dantas G (May 2014). "Bacterial phylogeny structures soil resistomes across habitats". Nature. 509 (7502): 612–6. Bibcode:2014Natur.509..612F. doi:10.1038/nature13377. PMC   4079543 . PMID   24847883.
  15. Breidenstein EB, de la Fuente-Núñez C, Hancock RE (August 2011). "Pseudomonas aeruginosa: all roads lead to resistance". Trends in Microbiology. 19 (8): 419–26. doi:10.1016/j.tim.2011.04.005. PMID   21664819.
  16. Aguirre de Cárcer D (September 2018). "The human gut pan-microbiome presents a compositional core formed by discrete phylogenetic units". Scientific Reports. 8 (1): 14069. Bibcode:2018NatSR...814069A. doi: 10.1038/s41598-018-32221-8 . PMC   6145917 . PMID   30232462.