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What makes an E.coli an E.coli, genotype or phenotype?

What makes an E.coli an E.coli, genotype or phenotype?


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According to this paper, among 61 strains of E. coli they studied only 6% of the genes are common in all. Which means that the overwhelming majority of the genes are not shared.

And wikipedia defines E. coli like this:

… is a Gram-negative, facultative anaerobic, rod-shaped, coliform bacterium of the genus Escherichia that is commonly found in the lower intestine of warm-blooded organisms (endotherms).

Which is a phenotypic definition. My question is: what defines E. coli as a species: its genotype or its phenotype?


The context for identifying E. coli is primarily clinical Microbiology, and in the clinical lab the identification is primarily phenotypic, based on various properties such as growth and morphology on selective media, Gram stain appearance, biochemical characteristics, etc - only under unusual circumstances is genetic testing done. The latter is problematic because of extreme genetic diversity within the species and some overlap with others (even other genera).

The problems with the notion of "species" in E. coli in the context of 16s sequencing, horizontal gene transfer, mobile genetic elements, plasmids, etc is discussed at some length in Quammen's recent book The Tangled Tree.

For now, phenotypic species identification is the norm, as illustrated by the "Nomenclature" guidance to authors of the Journal of Bacteriology, a publication of the American Society for Microbiology.


Surely both. Nowadays, with molecular technics avaiable with low effort, the typing is mainly done with genotyping. This can be done using the 16S rRNA gene, which is composed by hyper-variable regions, as reported in picture. This choice is justified because this gene is highly conserved into the bacterial phylum, giving perhaphs variation into some regions due to evolution. This concept is explained by the term "molecular clock" in evolutionary biology.

By designing specific primers (they already exists for more species) you could obtain only amplification by E.coli cells. This is just an example, exportable also to other bacterial species: by analyzing other conserved phenotypes for every strains of this species, is possible to do also some real-time PCR using other regions of the genome. Remember always that isolation and, by so, phenotyping is required while doing bacterial identification; the genotyping is the fastest and most accurate way to the first recognition step.


I happened to encounter a related problem recently in answering a question regarding a paper on virus classification. I am not a microbiologist, so this answer may be flawed, however it raises a point that I don't think has been made in the other answers. I welcome corrections.

First, however, it is obvious that bacteria were identified many, many years before their sequences were available, and, as indicated in the answer by @Argalatyr, classification could only be on phenotypic characteristics. The imprecision of this is acknowledged in a statement in a 2000 review article by Dijkshoorn et al. 'Strain, clone and species: comments on three basic concepts of bacteriology':

“A species consists of strains of common origin which are more similar to each other than they are to any other strain.”

The paper I came across previously was by Bobay and Ochman (2018) in which they state:

“Members of a biological species are defined by their ability to exchange genetic material

This definition - by its nature genotypic - clearly predates the DNA sequencing era. (In asexual organisms like bacteria, exchange of genetic material can occur by recombination of DNA.)

It should also be mentioned that this definition applied to bacteria does not require members of the same species to have the same number of genes (the concern of the question), only that they can recombine.

In their paper Dijkshoorn et al. go on to discuss current efforts to correlate what, I assume, is this accepted definition with DNA-based comparisons - 16S rRNA sequencing and overall DNA percentage identity.

“Recently, a comparison of DNA-DNA pairing data and 16S rRNA similarity data showed that strains with rRNA similarity less than c. 97% generally showed no significant DNA-DNA reassociation and thus belong to different species. Similarity >97% may or may not indicate close relationship. The use of this percentage as a rule of thumb has in many cases made rRNA sequencing replace the more cumbersome DNA-DNA pairing technique for the creation of new species. At present, either the 70% or the 97% rule is used to underpin most proposals for new species.”

The moral would seem to be that we have reached a stage where it is cheaper and easier to try to define species from DNA sequencing that to go into the laboratory and perform experiments to see whether they can exchange genetic material.


Phenotypic and genotypic characterization of enteroaggregative Escherichia coli isolates from pediatric population in Pakistan

Enteroaggregative Escherichia coli (EAEC) are a leading cause of diarrhea among children. The objective of this study was to define the frequency of EAEC among diarrheal children from flood-affected areas as well as sporadic cases, determine multidrug resistance, and evaluation of virulence using an in vivo model of pathogenesis. Stool samples were collected from 225 diarrheal children from 2010 to 2011 from flood-affected areas as well as from sporadic cases in Pakistan. Identified EAEC isolates were characterized by phylogrouping, antibiotic resistance patterns including the extended-spectrum beta lactamase spectrum, single nucleotide polymorphism detection in gyrA and parC, and virulence potential using wax worm, G. mellonella. A total of 35 (12.5%) confirmed EAEC isolates were identified among 225 E. coli isolates. EAEC isolates displayed high resistance to tetracycline, ampicillin, and cefaclor. A total of 34.28% were ESBL positive. Single nucleotide polymorphism detection revealed 37.14% and 68.57% isolates were positive for SNPs in gyrA (A660 -T660 ) and parC (C330 -T330 ), respectively. Phylogrouping revealed that B2 phylogroup was more prevalent among all EAEC isolates tested followed by D, A, B1, and non-typeable (NT). Infection of G. mellonella with EAEC showed that killing infective dose was 100% higher than E. coli DH5 alpha control. EAEC are prevalent among Pakistani children with diarrhea, they are highly resistant to antibiotics, and predominantly fall into B2 phylogroup. Epidemiologic surveillance of EAEC and other E. coli pathotypes is critical to assess not only the role of these pathogens in diarrheal disease but also to determine the extent of multidrug resistance among the population.

Keywords: Enteroaggregative Escherichia coli antibiotic resistance extended-spectrum beta lactamases phylogroups single nucleotide polymorphism virulence potential.


Introduction

A goal of systems biology has been to understand how phenotype originates from genotype. The phenotype of a cell is determined by complex regulation of metabolism, gene expression, and cell signaling. Understanding the connection between phenotype and genotype is crucial to understanding disease and for engineering biology 1 . Computational models are particularly well suited to studying this problem, as they can synthesize and organize diverse and complex data in a predictive framework, but detailed experimental studies including many samples are needed to understand interactions between different types of omics data 2 . Much effort is currently being spent on understanding how to best integrate information collected about multiple cellular subsystems that is derived from different types of high-throughput measurements. For example, there are many proposed approaches for relating gene expression and protein abundances, focusing on integrative, whole-cell models 2,3,4,5 .

Given the growing interest in integrative modeling approaches, there is a pressing need for high quality genome-scale data that is comparable across cellular subsystems and reflects many different external conditions. E. coli is an ideal organism to study genome-wide, multi-level regulatory effects of external conditions, since it is well adapted to the laboratory environment 6 and was one of the first organisms studied at the whole-genome level 7 . There have been a number of studies of the E. coli transcriptome and/or proteome in response to different growth conditions. For example, in cells growing at high density, expression of most amino acid biosynthesis genes is down-regulated and expression of chaperones is up-regulated, suggesting stresses that these cells experience 8 . Exposure of E. coli to reduced temperature leads to changes in gene-expression patterns consistent with reduced metabolism and growth 9 . Under long-term glucose starvation, mRNAs are generally down-regulated while the protein response is more varied 10 . Specifically, the copy numbers of proteins involved in energy-intensive processes decline whereas those of proteins involved in nutrient metabolism remain constant, likely to provide the cell with the ability to jump-start metabolism when nutrients become available again. A few other larger-scale studies have measured mRNA and/or protein abundances under multiple conditions 11,12,13,14 .

Here, we provide a systematic analysis of E. coli gene expression under a wide variety of different conditions. We measure both mRNA and protein abundances, at exponential and stationary phases, for growth conditions including different carbon sources and different salt stresses. We find that mRNAs and proteins display divergent responses to the different growth conditions. Further, growth phase yields more systematic differences in gene expression than does either carbon source or salt stress, though this effect is more pronounced in mRNAs than in proteins. We expect that our data set will provide a rich resource for future modeling work.


Growth Rate

Bacteria typically grow much faster than more complex organisms. E. coli grows rapidly at a rate of one generation per 20 minutes under typical growth conditions.

This allows for the preparation of log-phase (logarithmic phase, or the period in which a population grows exponentially) cultures overnight with mid-way to maximum density.

Genetic experimental results in mere hours instead of several days, months, or years. Faster growth also means better production rates when cultures are used in scaled-up fermentation processes.


Contents

Type and morphology Edit

E. coli is a Gram-negative, facultative anaerobe (that makes ATP by aerobic respiration if oxygen is present, but is capable of switching to fermentation or anaerobic respiration if oxygen is absent) and nonsporulating bacterium. [17] Cells are typically rod-shaped, and are about 2.0 μm long and 0.25–1.0 μm in diameter, with a cell volume of 0.6–0.7 μm 3 . [18] [19] [20]

E. coli stains Gram-negative because its cell wall is composed of a thin peptidoglycan layer and an outer membrane. During the staining process, E. coli picks up the color of the counterstain safranin and stains pink. The outer membrane surrounding the cell wall provides a barrier to certain antibiotics such that E. coli is not damaged by penicillin. [15]

Strains that possess flagella are motile. The flagella have a peritrichous arrangement. [21] It also attaches and effaces to the microvilli of the intestines via an adhesion molecule known as intimin. [22]

Metabolism Edit

E. coli can live on a wide variety of substrates and uses mixed acid fermentation in anaerobic conditions, producing lactate, succinate, ethanol, acetate, and carbon dioxide. Since many pathways in mixed-acid fermentation produce hydrogen gas, these pathways require the levels of hydrogen to be low, as is the case when E. coli lives together with hydrogen-consuming organisms, such as methanogens or sulphate-reducing bacteria. [23]

In addition, E. coli's metabolism can be rewired to solely use CO2 as the source of carbon for biomass production. In other words, this obligate heterotroph's metabolism can be altered to display autotrophic capabilities by heterologously expressing carbon fixation genes as well as formate dehydrogenase and conducting laboratory evolution experiments. This may be done by using formate to reduce electron carriers and supply the ATP required in anabolic pathways inside of these synthetic autotrophs. [24]

E. coli have three native glycolytic pathways: EMPP, EDP, and OPPP. The EMPP employs ten enzymatic steps to yield two pyruvates, two ATP, and two NADH per glucose molecule while OPPP serves as an oxidation route for NADPH synthesis. Although the EDP is the more thermodynamically favorable of the three pathways, E. coli do not use the EDP for glucose metabolism, relying mainly on the EMPP and the OPPP. The EDP mainly remains inactive except for during growth with gluconate. [25]

Catabolite Repression Edit

When growing in the presence of a mixture of sugars, bacteria will often consume the sugars sequentially through a process known as catabolite repression. By repressing the expression of the genes involved in metabolizing the less preferred sugars, cells will usually first consume the sugar yielding the highest growth rate, followed by the sugar yielding the next highest growth rate, and so on. In doing so the cells ensure that their limited metabolic resources are being used to maximize the rate of growth. The well-used example of this with E. coli involves the growth of the bacterium on glucose and lactose, where E. coli will consume glucose before lactose. Catabolite repression has also been observed in E.coli in the presence of other non-glucose sugars, such as arabinose and xylose, sorbitol, rhamnose, and ribose. In E. coli, glucose catabolite repression is regulated by the phosphotransferase system, a multi-protein phosphorylation cascade that couples glucose uptake and metabolism. [26]

Culture growth Edit

Optimum growth of E. coli occurs at 37 °C (98.6 °F), but some laboratory strains can multiply at temperatures up to 49 °C (120 °F). [27] E. coli grows in a variety of defined laboratory media, such as lysogeny broth, or any medium that contains glucose, ammonium phosphate monobasic, sodium chloride, magnesium sulfate, potassium phosphate dibasic, and water. Growth can be driven by aerobic or anaerobic respiration, using a large variety of redox pairs, including the oxidation of pyruvic acid, formic acid, hydrogen, and amino acids, and the reduction of substrates such as oxygen, nitrate, fumarate, dimethyl sulfoxide, and trimethylamine N-oxide. [28] E. coli is classified as a facultative anaerobe. It uses oxygen when it is present and available. It can, however, continue to grow in the absence of oxygen using fermentation or anaerobic respiration. The ability to continue growing in the absence of oxygen is an advantage to bacteria because their survival is increased in environments where water predominates. [15]

Cell cycle Edit

The bacterial cell cycle is divided into three stages. The B period occurs between the completion of cell division and the beginning of DNA replication. The C period encompasses the time it takes to replicate the chromosomal DNA. The D period refers to the stage between the conclusion of DNA replication and the end of cell division. [29] The doubling rate of E. coli is higher when more nutrients are available. However, the length of the C and D periods do not change, even when the doubling time becomes less than the sum of the C and D periods. At the fastest growth rates, replication begins before the previous round of replication has completed, resulting in multiple replication forks along the DNA and overlapping cell cycles. [30]

The number of replication forks in fast growing E. coli typically follows 2n (n = 1, 2 or 3). This only happens if replication is initiated simultaneously from all origins of replications, and is referred to as synchronous replication. However, not all cells in a culture replicate synchronously. In this case cells do not have multiples of two replication forks. Replication initiation is then referred to being asynchronous. [31] However, asynchrony can be caused by mutations to for instance DnaA [31] or DnaA initiator-associating protein DiaA. [32]

Genetic adaptation Edit

E. coli and related bacteria possess the ability to transfer DNA via bacterial conjugation or transduction, which allows genetic material to spread horizontally through an existing population. The process of transduction, which uses the bacterial virus called a bacteriophage, [33] is where the spread of the gene encoding for the Shiga toxin from the Shigella bacteria to E. coli helped produce E. coli O157:H7, the Shiga toxin-producing strain of E. coli.

E. coli encompasses an enormous population of bacteria that exhibit a very high degree of both genetic and phenotypic diversity. Genome sequencing of many isolates of E. coli and related bacteria shows that a taxonomic reclassification would be desirable. However, this has not been done, largely due to its medical importance, [34] and E. coli remains one of the most diverse bacterial species: only 20% of the genes in a typical E. coli genome is shared among all strains. [35]

In fact, from the more constructive point of view, the members of genus Shigella (S. dysenteriae, S. flexneri, S. boydii, and S. sonnei) should be classified as E. coli strains, a phenomenon termed taxa in disguise. [36] Similarly, other strains of E. coli (e.g. the K-12 strain commonly used in recombinant DNA work) are sufficiently different that they would merit reclassification.

A strain is a subgroup within the species that has unique characteristics that distinguish it from other strains. These differences are often detectable only at the molecular level however, they may result in changes to the physiology or lifecycle of the bacterium. For example, a strain may gain pathogenic capacity, the ability to use a unique carbon source, the ability to take upon a particular ecological niche, or the ability to resist antimicrobial agents. Different strains of E. coli are often host-specific, making it possible to determine the source of fecal contamination in environmental samples. [12] [13] For example, knowing which E. coli strains are present in a water sample allows researchers to make assumptions about whether the contamination originated from a human, another mammal, or a bird.

Serotypes Edit

A common subdivision system of E. coli, but not based on evolutionary relatedness, is by serotype, which is based on major surface antigens (O antigen: part of lipopolysaccharide layer H: flagellin K antigen: capsule), e.g. O157:H7). [37] It is, however, common to cite only the serogroup, i.e. the O-antigen. At present, about 190 serogroups are known. [38] The common laboratory strain has a mutation that prevents the formation of an O-antigen and is thus not typeable.

Genome plasticity and evolution Edit

Like all lifeforms, new strains of E. coli evolve through the natural biological processes of mutation, gene duplication, and horizontal gene transfer in particular, 18% of the genome of the laboratory strain MG1655 was horizontally acquired since the divergence from Salmonella. [39] E. coli K-12 and E. coli B strains are the most frequently used varieties for laboratory purposes. Some strains develop traits that can be harmful to a host animal. These virulent strains typically cause a bout of diarrhea that is often self-limiting in healthy adults but is frequently lethal to children in the developing world. [40] More virulent strains, such as O157:H7, cause serious illness or death in the elderly, the very young, or the immunocompromised. [40] [41]

The genera Escherichia and Salmonella diverged around 102 million years ago (credibility interval: 57–176 mya), which coincides with the divergence of their hosts: the former being found in mammals and the latter in birds and reptiles. [42] This was followed by a split of an Escherichia ancestor into five species (E. albertii, E. coli, E. fergusonii, E. hermannii, and E. vulneris). The last E. coli ancestor split between 20 and 30 million years ago. [43]

The long-term evolution experiments using E. coli, begun by Richard Lenski in 1988, have allowed direct observation of genome evolution over more than 65,000 generations in the laboratory. [44] For instance, E. coli typically do not have the ability to grow aerobically with citrate as a carbon source, which is used as a diagnostic criterion with which to differentiate E. coli from other, closely, related bacteria such as Salmonella. In this experiment, one population of E. coli unexpectedly evolved the ability to aerobically metabolize citrate, a major evolutionary shift with some hallmarks of microbial speciation.

In the microbial world, a relationship of predation can be established similar to that observed in the animal world. Considered, it has been seen that E. coli is the prey of multiple generalist predators, such as Myxococcus xanthus. In this predator-prey relationship, a parallel evolution of both species is observed through genomic and phenotypic modifications, in the case of E. coli the modifications are modified in two aspects involved in their virulence such as mucoid production (excessive production of exoplasmic acid alginate ) and the suppression of the OmpT gene, producing in future generations a better adaptation of one of the species that is counteracted by the evolution of the other, following a co-evolutionary model demonstrated by the Red Queen hypothesis. [45]

Neotype strain Edit

E. coli is the type species of the genus (Escherichia) and in turn Escherichia is the type genus of the family Enterobacteriaceae, where the family name does not stem from the genus Enterobacter + "i" (sic.) + "aceae", but from "enterobacterium" + "aceae" (enterobacterium being not a genus, but an alternative trivial name to enteric bacterium). [46] [47]

The original strain described by Escherich is believed to be lost, consequently a new type strain (neotype) was chosen as a representative: the neotype strain is U5/41 T , [48] also known under the deposit names DSM 30083, [49] ATCC 11775, [50] and NCTC 9001, [51] which is pathogenic to chickens and has an O1:K1:H7 serotype. [52] However, in most studies, either O157:H7, K-12 MG1655, or K-12 W3110 were used as a representative E. coli. The genome of the type strain has only lately been sequenced. [48]

Phylogeny of E. coli strains Edit

Many strains belonging to this species have been isolated and characterised. In addition to serotype (vide supra), they can be classified according to their phylogeny, i.e. the inferred evolutionary history, as shown below where the species is divided into six groups. [53] [54] Particularly the use of whole genome sequences yields highly supported phylogenies. Based on such data, five subspecies of E. coli were distinguished. [48]

The link between phylogenetic distance ("relatedness") and pathology is small, [48] e.g. the O157:H7 serotype strains, which form a clade ("an exclusive group")—group E below—are all enterohaemorragic strains (EHEC), but not all EHEC strains are closely related. In fact, four different species of Shigella are nested among E. coli strains (vide supra), while E. albertii and E. fergusonii are outside this group. Indeed, all Shigella species were placed within a single subspecies of E. coli in a phylogenomic study that included the type strain, [48] and for this reason an according reclassification is difficult. All commonly used research strains of E. coli belong to group A and are derived mainly from Clifton's K-12 strain (λ + F + O16) and to a lesser degree from d'Herelle's Bacillus coli strain (B strain)(O7).

E. coli S88 (O45:K1. Extracellular pathogenic)

E. coli UMN026 (O17:K52:H18. Extracellular pathogenic)

E. coli (O19:H34. Extracellular pathogenic)

E. coli (O7:K1. Extracellular pathogenic)

E. coli GOS1 (O104:H4 EAHEC) German 2011 outbreak

E. coli ATCC8739 (O146. Crook's E.coli used in phage work in the 1950s)

E. coli K-12 W3110 (O16. λ − F − "wild type" molecular biology strain)

E. coli K-12 DH10b (O16. high electrocompetency molecular biology strain)

E. coli K-12 DH1 (O16. high chemical competency molecular biology strain)

E. coli K-12 MG1655 (O16. λ − F − "wild type" molecular biology strain)

E. coli BW2952 (O16. competent molecular biology strain)

E. coli B REL606 (O7. high competency molecular biology strain)

E. coli BL21-DE3 (O7. expression molecular biology strain with T7 polymerase for pET system)

The first complete DNA sequence of an E. coli genome (laboratory strain K-12 derivative MG1655) was published in 1997. It is a circular DNA molecule 4.6 million base pairs in length, containing 4288 annotated protein-coding genes (organized into 2584 operons), seven ribosomal RNA (rRNA) operons, and 86 transfer RNA (tRNA) genes. Despite having been the subject of intensive genetic analysis for about 40 years, many of these genes were previously unknown. The coding density was found to be very high, with a mean distance between genes of only 118 base pairs. The genome was observed to contain a significant number of transposable genetic elements, repeat elements, cryptic prophages, and bacteriophage remnants. [55]

More than three hundred complete genomic sequences of Escherichia and Shigella species are known. The genome sequence of the type strain of E. coli was added to this collection before 2014. [48] Comparison of these sequences shows a remarkable amount of diversity only about 20% of each genome represents sequences present in every one of the isolates, while around 80% of each genome can vary among isolates. [35] Each individual genome contains between 4,000 and 5,500 genes, but the total number of different genes among all of the sequenced E. coli strains (the pangenome) exceeds 16,000. This very large variety of component genes has been interpreted to mean that two-thirds of the E. coli pangenome originated in other species and arrived through the process of horizontal gene transfer. [56]

Genes in E. coli are usually named by 4-letter acronyms that derive from their function (when known) and italicized. For instance, recA is named after its role in homologous recombination plus the letter A. Functionally related genes are named recB, recC, recD etc. The proteins are named by uppercase acronyms, e.g. RecA, RecB, etc. When the genome of E. coli was sequenced, all genes were numbered (more or less) in their order on the genome and abbreviated by b numbers, such as b2819 (= recD). The "b" names were created after Fred Blattner, who led the genome sequence effort. [55] Another numbering system was introduced with the sequence of another E. coli strain, W3110, which was sequenced in Japan and hence uses numbers starting by JW. (Japanese W3110), e.g. JW2787 (= recD). [57] Hence, recD = b2819 = JW2787. Note, however, that most databases have their own numbering system, e.g. the EcoGene database [58] uses EG10826 for recD. Finally, ECK numbers are specifically used for alleles in the MG1655 strain of E. coli K-12. [58] Complete lists of genes and their synonyms can be obtained from databases such as EcoGene or Uniprot.

Proteome Edit

Several studies have investigated the proteome of E. coli. By 2006, 1,627 (38%) of the 4,237 open reading frames (ORFs) had been identified experimentally. [59] The 4,639,221–base pair sequence of Escherichia coli K-12 is presented. Of 4288 protein-coding genes annotated, 38 percent have no attributed function. Comparison with five other sequenced microbes reveals ubiquitous as well as narrowly distributed gene families many families of similar genes within E. coli are also evident. The largest family of paralogous proteins contains 80 ABC transporters. The genome as a whole is strikingly organized with respect to the local direction of replication guanines, oligonucleotides possibly related to replication and recombination, and most genes are so oriented. The genome also contains insertion sequence (IS) elements, phage remnants, and many other patches of unusual composition indicating genome plasticity through horizontal transfer. [55]

Interactome Edit

The interactome of E. coli has been studied by affinity purification and mass spectrometry (AP/MS) and by analyzing the binary interactions among its proteins.

Protein complexes. A 2006 study purified 4,339 proteins from cultures of strain K-12 and found interacting partners for 2,667 proteins, many of which had unknown functions at the time. [60] A 2009 study found 5,993 interactions between proteins of the same E. coli strain, though these data showed little overlap with those of the 2006 publication. [61]

Binary interactions. Rajagopala et al. (2014) have carried out systematic yeast two-hybrid screens with most E. coli proteins, and found a total of 2,234 protein-protein interactions. [62] This study also integrated genetic interactions and protein structures and mapped 458 interactions within 227 protein complexes.

E. coli belongs to a group of bacteria informally known as coliforms that are found in the gastrointestinal tract of warm-blooded animals. [63] E. coli normally colonizes an infant's gastrointestinal tract within 40 hours of birth, arriving with food or water or from the individuals handling the child. In the bowel, E. coli adheres to the mucus of the large intestine. It is the primary facultative anaerobe of the human gastrointestinal tract. [64] (Facultative anaerobes are organisms that can grow in either the presence or absence of oxygen.) As long as these bacteria do not acquire genetic elements encoding for virulence factors, they remain benign commensals. [65]

Therapeutic use Edit

Due to the low cost and speed with which it can be grown and modified in laboratory settings, E. coli is a popular expression platform for the production of recombinant proteins used in therapeutics. One advantage to using E. coli over another expression platform is that E. coli naturally does not export many proteins into the periplasm, making it easier to recover a protein of interest without cross-contamination. [66] The E. coli K-12 strains and their derivatives (DH1, DH5α, MG1655, RV308 and W3110) are the strains most widely used by the biotechnology industry. [67] Nonpathogenic E. coli strain Nissle 1917 (EcN), (Mutaflor) and E. coli O83:K24:H31 (Colinfant) [68] [69] ) are used as probiotic agents in medicine, mainly for the treatment of various gastrointestinal diseases, [70] including inflammatory bowel disease. [71] It is thought that the EcN strain might impede the growth of opportunistic pathogens, including Salmonella and other coliform enteropathogens, through the production of microcin proteins the production of siderophores. [72]

Most E. coli strains do not cause disease, naturally living in the gut, [73] but virulent strains can cause gastroenteritis, urinary tract infections, neonatal meningitis, hemorrhagic colitis, and Crohn's disease. Common signs and symptoms include severe abdominal cramps, diarrhea, hemorrhagic colitis, vomiting, and sometimes fever. In rarer cases, virulent strains are also responsible for bowel necrosis (tissue death) and perforation without progressing to hemolytic-uremic syndrome, peritonitis, mastitis, sepsis, and Gram-negative pneumonia. Very young children are more susceptible to develop severe illness, such as hemolytic uremic syndrome however, healthy individuals of all ages are at risk to the severe consequences that may arise as a result of being infected with E. coli. [64] [74] [75] [76]

Some strains of E. coli, for example O157:H7, can produce Shiga toxin (classified as a bioterrorism agent). The Shiga toxin causes inflammatory responses in target cells of the gut, leaving behind lesions which result in the bloody diarrhea that is a symptom of a Shiga toxin-producing E. coli (STEC) infection. This toxin further causes premature destruction of the red blood cells, which then clog the body's filtering system, the kidneys, in some rare cases (usually in children and the elderly) causing hemolytic-uremic syndrome (HUS), which may lead to kidney failure and even death. Signs of hemolytic uremic syndrome include decreased frequency of urination, lethargy, and paleness of cheeks and inside the lower eyelids. In 25% of HUS patients, complications of nervous system occur, which in turn causes strokes. In addition, this strain causes the buildup of fluid (since the kidneys do not work), leading to edema around the lungs, legs, and arms. This increase in fluid buildup especially around the lungs impedes the functioning of the heart, causing an increase in blood pressure. [77] [22] [78] [79] [80] [75] [76]

Uropathogenic E. coli (UPEC) is one of the main causes of urinary tract infections. [81] It is part of the normal microbiota in the gut and can be introduced in many ways. In particular for females, the direction of wiping after defecation (wiping back to front) can lead to fecal contamination of the urogenital orifices. Anal intercourse can also introduce this bacterium into the male urethra, and in switching from anal to vaginal intercourse, the male can also introduce UPEC to the female urogenital system.

Enterotoxigenic E. coli (ETEC) is the most common cause of traveler's diarrhea, with as many as 840 million cases worldwide in developing countries each year. The bacteria, typically transmitted through contaminated food or drinking water, adheres to the intestinal lining, where it secretes either of two types of enterotoxins, leading to watery diarrhea. The rate and severity of infections are higher among children under the age of five, including as many as 380,000 deaths annually. [82]

In May 2011, one E. coli strain, O104:H4, was the subject of a bacterial outbreak that began in Germany. Certain strains of E. coli are a major cause of foodborne illness. The outbreak started when several people in Germany were infected with enterohemorrhagic E. coli (EHEC) bacteria, leading to hemolytic-uremic syndrome (HUS), a medical emergency that requires urgent treatment. The outbreak did not only concern Germany, but also 15 other countries, including regions in North America. [83] On 30 June 2011, the German Bundesinstitut für Risikobewertung (BfR) (Federal Institute for Risk Assessment, a federal institute within the German Federal Ministry of Food, Agriculture and Consumer Protection) announced that seeds of fenugreek from Egypt were likely the cause of the EHEC outbreak. [84]

Some studies have demonstrated an absence of E.coli in the gut flora of subjects with the metabolic disorder Phenylketonuria. It is hypothesized that the absence of these normal bacterium impairs the production of the key vitamins B2 (riboflavin) and K2 (menaquinone) - vitamins which are implicated in many physiological roles in humans such as cellular and bone metabolism - and so contributes to the disorder. [85]

Incubation period Edit

The time between ingesting the STEC bacteria and feeling sick is called the "incubation period". The incubation period is usually 3–4 days after the exposure, but may be as short as 1 day or as long as 10 days. The symptoms often begin slowly with mild belly pain or non-bloody diarrhea that worsens over several days. HUS, if it occurs, develops an average 7 days after the first symptoms, when the diarrhea is improving. [86]

Diagnosis Edit

Diagnosis of infectious diarrhea and identification of antimicrobial resistance is performed using a stool culture with subsequent antibiotic sensitivity testing. It requires a minimum of 2 days and maximum of several weeks to culture gastrointestinal pathogens. The sensitivity (true positive) and specificity (true negative) rates for stool culture vary by pathogen, although a number of human pathogens can not be cultured. For culture-positive samples, antimicrobial resistance testing takes an additional 12-24 hours to perform.

Current point of care molecular diagnostic tests can identify E. coli and antimicrobial resistance in the identified strains much faster than culture and sensitivity testing. Microarray-based platforms can identify specific pathogenic strains of E. coli and E. coli-specific AMR genes in two hours or less with high sensitivity and specificity, but the size of the test panel (i.e., total pathogens and antimicrobial resistance genes) is limited. Newer metagenomics-based infectious disease diagnostic platforms are currently being developed to overcome the various limitations of culture and all currently available molecular diagnostic technologies.

Treatment Edit

The mainstay of treatment is the assessment of dehydration and replacement of fluid and electrolytes. Administration of antibiotics has been shown to shorten the course of illness and duration of excretion of enterotoxigenic E. coli (ETEC) in adults in endemic areas and in traveller's diarrhea, though the rate of resistance to commonly used antibiotics is increasing and they are generally not recommended. [87] The antibiotic used depends upon susceptibility patterns in the particular geographical region. Currently, the antibiotics of choice are fluoroquinolones or azithromycin, with an emerging role for rifaximin. Oral rifaximin, a semisynthetic rifamycin derivative, is an effective and well-tolerated antibacterial for the management of adults with non-invasive traveller's diarrhea. Rifaximin was significantly more effective than placebo and no less effective than ciprofloxacin in reducing the duration of diarrhea. While rifaximin is effective in patients with E. coli-predominant traveller's diarrhea, it appears ineffective in patients infected with inflammatory or invasive enteropathogens. [88]

Prevention Edit

ETEC is the type of E. coli that most vaccine development efforts are focused on. Antibodies against the LT and major CFs of ETEC provide protection against LT-producing, ETEC-expressing homologous CFs. Oral inactivated vaccines consisting of toxin antigen and whole cells, i.e. the licensed recombinant cholera B subunit (rCTB)-WC cholera vaccine Dukoral, have been developed. There are currently no licensed vaccines for ETEC, though several are in various stages of development. [89] In different trials, the rCTB-WC cholera vaccine provided high (85–100%) short-term protection. An oral ETEC vaccine candidate consisting of rCTB and formalin inactivated E. coli bacteria expressing major CFs has been shown in clinical trials to be safe, immunogenic, and effective against severe diarrhoea in American travelers but not against ETEC diarrhoea in young children in Egypt. A modified ETEC vaccine consisting of recombinant E. coli strains over-expressing the major CFs and a more LT-like hybrid toxoid called LCTBA, are undergoing clinical testing. [90] [91]

Other proven prevention methods for E. coli transmission include handwashing and improved sanitation and drinking water, as transmission occurs through fecal contamination of food and water supplies. Additionally, thoroughly cooking meat and avoiding consumption of raw, unpasteurized beverages, such as juices and milk are other proven methods for preventing E.coli. Lastly, avoid cross-contamination of utensils and work spaces when preparing food. [92]

Because of its long history of laboratory culture and ease of manipulation, E. coli plays an important role in modern biological engineering and industrial microbiology. [93] The work of Stanley Norman Cohen and Herbert Boyer in E. coli, using plasmids and restriction enzymes to create recombinant DNA, became a foundation of biotechnology. [94]

E. coli is a very versatile host for the production of heterologous proteins, [95] and various protein expression systems have been developed which allow the production of recombinant proteins in E. coli. Researchers can introduce genes into the microbes using plasmids which permit high level expression of protein, and such protein may be mass-produced in industrial fermentation processes. One of the first useful applications of recombinant DNA technology was the manipulation of E. coli to produce human insulin. [96]

Many proteins previously thought difficult or impossible to be expressed in E. coli in folded form have been successfully expressed in E. coli. For example, proteins with multiple disulphide bonds may be produced in the periplasmic space or in the cytoplasm of mutants rendered sufficiently oxidizing to allow disulphide-bonds to form, [97] while proteins requiring post-translational modification such as glycosylation for stability or function have been expressed using the N-linked glycosylation system of Campylobacter jejuni engineered into E. coli. [98] [99] [100]

Modified E. coli cells have been used in vaccine development, bioremediation, production of biofuels, [101] lighting, and production of immobilised enzymes. [95] [102]

Strain K-12 is a mutant form of E. coli that over-expresses the enzyme Alkaline Phosphatase (ALP). [103] The mutation arises due to a defect in the gene that constantly codes for the enzyme. A gene that is producing a product without any inhibition is said to have constitutive activity. This particular mutant form is used to isolate and purify the aforementioned enzyme. [103]

Strain OP50 of Escherichia coli is used for maintenance of Caenorhabditis elegans cultures.

Strain JM109 is a mutant form of E. coli that is recA and endA deficient. The strain can be utilized for blue/white screening when the cells carry the fertility factor episome [104] Lack of recA decreases the possibility of unwanted restriction of the DNA of interest and lack of endA inhibit plasmid DNA decomposition. Thus, JM109 is useful for cloning and expression systems.

Model organism Edit

E. coli is frequently used as a model organism in microbiology studies. Cultivated strains (e.g. E. coli K12) are well-adapted to the laboratory environment, and, unlike wild-type strains, have lost their ability to thrive in the intestine. Many laboratory strains lose their ability to form biofilms. [105] [106] These features protect wild-type strains from antibodies and other chemical attacks, but require a large expenditure of energy and material resources. E. coli is often used as a representative microorganism in the research of novel water treatment and sterilisation methods, including photocatalysis. By standard plate count methods, following sequential dilutions, and growth on agar gel plates, the concentration of viable organisms or CFUs (Colony Forming Units), in a known volume of treated water can be evaluated, allowing the comparative assessment of materials performance. [107]

In 1946, Joshua Lederberg and Edward Tatum first described the phenomenon known as bacterial conjugation using E. coli as a model bacterium, [108] and it remains the primary model to study conjugation. [109] E. coli was an integral part of the first experiments to understand phage genetics, [110] and early researchers, such as Seymour Benzer, used E. coli and phage T4 to understand the topography of gene structure. [111] Prior to Benzer's research, it was not known whether the gene was a linear structure, or if it had a branching pattern. [112]

E. coli was one of the first organisms to have its genome sequenced the complete genome of E. coli K12 was published by Science in 1997 [55]

From 2002 to 2010, a team at the Hungarian Academy of Science created a strain of Escherichia coli called MDS42, which is now sold by Scarab Genomics of Madison, WI under the name of "Clean Genome. E.coli", [113] where 15% of the genome of the parental strain (E. coli K-12 MG1655) were removed to aid in molecular biology efficiency, removing IS elements, pseudogenes and phages, resulting in better maintenance of plasmid-encoded toxic genes, which are often inactivated by transposons. [114] [115] [116] Biochemistry and replication machinery were not altered.

By evaluating the possible combination of nanotechnologies with landscape ecology, complex habitat landscapes can be generated with details at the nanoscale. [117] On such synthetic ecosystems, evolutionary experiments with E. coli have been performed to study the spatial biophysics of adaptation in an island biogeography on-chip.

Studies are also being performed attempting to program E. coli to solve complicated mathematics problems, such as the Hamiltonian path problem. [118]

In other studies, non-pathogenic E. coli has been used as a model microorganism towards understanding the effects of simulated microgravity (on Earth) on the same. [119] [120]

In 1885, the German-Austrian pediatrician Theodor Escherich discovered this organism in the feces of healthy individuals. He called it Bacterium coli commune because it is found in the colon. Early classifications of prokaryotes placed these in a handful of genera based on their shape and motility (at that time Ernst Haeckel's classification of bacteria in the kingdom Monera was in place). [91] [121] [122]

Bacterium coli was the type species of the now invalid genus Bacterium when it was revealed that the former type species ("Bacterium triloculare") was missing. [123] Following a revision of Bacterium, it was reclassified as Bacillus coli by Migula in 1895 [124] and later reclassified in the newly created genus Escherichia, named after its original discoverer. [125]

In 1996, the world's worst to date outbreak of E. coli food poisoning occurred in Wishaw, Scotland, killing 21 people. [126] This death toll was exceeded in 2011, when the 2011 Germany E. coli O104:H4 outbreak, linked to organic fenugreek sprouts, killed 53 people.


What makes an E.coli an E.coli, genotype or phenotype? - Biology

1) 36 pts . Short answer section.

(a) 4 pt. What is meant by a helper transposon or a helper virus?

A helper element provides a function needed by a defective element in order to transpose or to grow. For example enhancer trap P-elements no longer carry transposase and require a helper to provide the enzyme. Similarly, defective retroviruses need a helper virus to provide the missing viral function

(b) 4 pt. Which proteins constitute the HIV receptor?

The CD4 and CCR-5 proteins together constitute the primary HIV receptor. Late in infection M-trophic viruses recognize a receptor composed of CD4 and CXCR-4.

(c) 8 pt. State whether the following best apply to E. coli lac , or yeast GAL regulation, or whether they are equally applicable.

(i ) Inducer inactivates a repressor, thus allowing an activator to function.

Applies to both. In lac , inducer inactivates LacI and CAP-cAMP can stimulate transcription. In the yeast GAL system, inducer inactivates GAL80 uncovering the activation domain of GAL4 and transcription of the GAL genes occurs.

(ii ) Mutations in the activator can bypass the effect of uninducible repressor mutants.

Applies to yeast GAL . GAL4 activators that cannot bind an uninducible version of GAL80 will express the GAL genes. An E. coli CAP* mutant will still be repressed

by an I S repressor.
(d)
6 pt. Predict the expression pattern of the lac operon in an E. coli merodiploid with genotype lacI Q /lacI -d . Explain your answer.

The strain will be inducible. lacI -d is a dominant negative mutation that functions as a poison subunit in the repressor tetramer leading to constitutive expression even when wild-type subunits are present. However, lacI Q produces 10-20-times the normal amount of wild-type repressor, meaning that the majority of repressor molecules in the I Q /I -d merodiploid cell will be composed of wild-type subunits and therefore be capable of binding DNA and being induced by IPTG.

(e) 8 pt. An enhancer trap screen have identified 5 independent fly lines that express ß-galactosidase in the developing trachea, or breathing tubes, of the fly. All 5 enhancer trap lines are viable when homozygous, and none cause tracheal defects. Explain what you could do to determine whether any of the enhancer trap lines affect a gene that is important for tracheal function or development.

It's possible that none of the P insertions has inactivated the gene. To see if the genes are important for tracheal function one needs to make loss-of-function mutations. This can be done by screening for imprecise excisions, or P-element-induced deletion derivatives of these genes. This can be done by exposing the flies to a transposase source and then looking for white-eyed ß- gal non-expressors. These canb e examined by Southern blotting to see if the gene has been deleted by imprecise excision. Once a deletion has been isolated for a particular gene, flies can be made homozygous for the deletion and their phenotypes examined. If the gene is important for viability flies homozygous for the P-induced deletions will not survive or will not develop normal trachea.

(f) 6 pt. Suggest two ways that a proto-oncogene can be converted into an active oncogene.

A protooncogene could be activated by a point mutation such as the one that makes the Ras kinase constitutively active.

Another way would be to alter the expression of an oncogene. Unregulated transcription of myc due to fusion of the gene and its promoter to a new enhancer can cause constitutive high-level expression of this cell-cycle activator.

2) 15 pts. The pheR100 deletion results in the constitutive expression of the phe operon ( pheRABCD) of a hypothetical Bacillus . DNA from wild-type strain pheR + and DNA from the pheR100 mutant were isolated an used in an in vitro transcription system containing only purified RNA polymerase, the DNAs, and rNTPs. The following results were obtained:

relative amount of pheABCD

a) The results of this experiment and the in vivo phenotype of pheR100 argue against the existence of a phe operon repressor. Why?

Since there is no repressor protein in the in vitro system, there should be no repression of either template. Both the wild-type and the deletion pheR100 DNAs should express equally well since the operator would be unbound in the case of wild-type or absent in the case o the deletion.

b) The results also argue against the existence of a positive activator protein. Why?

Because the in vitro system does not contain the activator protein, one would expect low-level expression for both templates. For the wild-type, the binding site is there, but unoccupied. For the mutant the site is missing and unoccupied.

c) Based on what you know about gene regulation in E. coli, suggest what sort of site is removed by the pheR100 mutation.

It seems that something serves as a barrier to transcription in the wild-type and that the pheR100 deletion removes the barrier. This suggests that the site is likely a transcription terminator or an attenuator.

3 ) 16 pts . The SOS DNA repair genes in E. coli are negatively regulated by the product of the lexA gene, called the LexA repressor. When a cell sustains extensive damage to its DNA, LexA repressor is inactivated and transcription of the SOS genes is increased dramatically.


One of the SOS genes is uvrA . You isolate a strain with constitutive expression of uvrA protein and name the mutation uvrA (con). Shown below is a diagram of the uvrA and lexA genes.

(a) Describe two different mutations that would result in a uvrA constitutive phenotype.

Mutations that inactivated lexA should lead to a constitutive uvrA phenotype as the uvrA gene will no longer be repressed. Mutations in the uvrA operator should also cause a constitutive uvrA phenotype as they would block the binding of LexA.

(b) Outline an experiment that would allow you to determine which of the two mutations you have isolated.

Make a partial diploid with the constitutive mutation and a wild-type lexA and uvrA genes. If lexA is mutated, it should be a recessive mutation and uvrA will be repressed and inducible by DNA damage. If the mutation is in the uvrA operator, uvrA will still be constitively expressed, as LexA will not bind the mutant copy of the gene.

One could also examine whether the other SOS genes are induced in the uvrA(con) strain. If they are it would imply that lexA is mutant, as the cis-acting uvrA operator mutation should only affect genes in the uvrA operon. If it appears to affect lexA , one should confirm this result by showing that the uvrA(con) allele is recessive to lexA + , to exclude the possibility that the constitutivity arises from another mutation, i.e. one that constitively expresses the inducing signal. Such mutations exist and are known as recA * .

4) 33 pts . A novel steroid hormone receptor (TaxR) has recently been identified. The receptor responds to the level of Test Anxiety Hormone circulating in the blood and mediates a variety of biological responses ranging from muscle twitching to complete repression of cerebral function.

By analogy, TaxR is suspected to contain four different protein domains: a hormone binding site, a region that interacts with the hsp90 protein, a DNA binding domain, and a transcriptional regulatory region. To map the TaxR protein domains a variety of TaxR deletion mutants were created using recombinant DNA techniques. These TaxR mutants were analyzed in cultured mammalian cells that carried a lacZ + reporter gene whose expression was controlled by four TRE sequences (TRE=Test Anxiety Hormone Receptor Element).

To monitor intracellular location , the mutant TaxR genes were fused to a gene encoding a protein called GFP (Green Fluorescent Protein). GFP is naturally fluorescent--that is, the protein glows bright green when stimulated with light.

The Tax-R derivatives were transformed into cells and assayed with or without Test Anxiety hormone. The results for the wild-type protein and for a full-length TaxR-GFP fusion are shown:

The domains of TaxR are labeled 1-4. GFP protein is shown in gray. Fluorescent cells and nuclei are gray. White indicates no fluorescence.

(a) 6 pts. Are the results consistent with those obtained for other steroid hormone receptors? Briefly explain why or why not.

Yes, the TaxR protein is cytoplasmic and inactive unless hormone is present. In response to hormone TaxR enters the nucleus and activates transcription. This is exactly the effect seen with the Glucocorticoid receptor.

4b) 15 pts . For each of the TaxR-GFP proteins diagrammed below assume: i) that region 1 is the transcriptional regulatory domain, ii) that region 2 contains the DNA binding domain, iii) that region 3 interacts with hsp90 protein, and iv) that region 4 binds Test Anxiety Hormone.

Fill in the expected results for the cell fluorescence and ß-gal activity assays given the assumptions listed above. Briefly explain your answers in the space to the right of each drawing.


4 c) 12 pts. Surprisingly TaxR appears not to interact with the hsp90 protein. Instead the data suggest it interacts with an unidentified protein thought to function analogously to hsp90.

Propose an experiment that would allow you to identify the TaxR-interacting hsp90 analog and to clone a cDNA encoding that protein. You many use any reasonable technique from the texts, the lecture, or your own experience. Your answer should provide sufficient detail to demonstrate that you understand the strategy and the techniques you employ.

Use the two-hybrid system to screen a cDNA library to find clones that interact with domain 3 of TaxR. (You should use domain 3 so that you don't recover proteins that bind to other domains of TaxR.)

First, make a fusion between domain 3 of TaxR and the lexA DNA binding domain.

Second make a random cDNA library fused to the activation domain of GAL4. The library should be made from mRNA from tissues that are known to express the cytoplasmic interacting protein. Given the biology of the response, a good choice would be a library made from the brain of a student with a minimal test anxiety response.

Introduce the lexA-domain3 plasmid and the library plasmids into a strain carrying a lacZ gene with a minimal promoter and multiple lexA operator sites.

Select for lacZ expression which indicates a protein-protein interaction between domain 3 and a library plasmid.

As shown in the drawing, only proteins that interact with domain 3 should induce the expression of lacZ .

To isolate the cDNA clone simply purify the strain expressing lacZ and isolate the library plasmid.

Extra credit . 6 pts . You have isolated a Tn10 insertion just upstream of the wild-type his operon following the protocol outlined in lecture. You would like to use this Tn10 to introduce a particular his - mutation (caused by a nonsense mutation in the his leader peptide) into a variety of strains with reduced tRNA His function, ie. hisS, hisT, hisU, hisR to see what effect these mutations have on the expression of the his operon carrying the leader peptide mutation.

Explain how you would do this.

Transduce the his - strain to tet R . Score the tet R transductants for the his - phenotype by plating the transductants on media with and without histidine.. Most of these will be His + since the Tn10 is closely linked but those that are tet R , his - now have the Tn10 tighlty linked to the his - mutation. This strain will now serve as a donor.

Grow transducing phage on the new tet R his - donor and transduce each of the recipient strains hisS , hisT , etc. to tet R . Nearly all of these will carry the his - mutation.

Now score the His phenotype for several of the resulting transductants to test for the interaction between the altered tRNA function and the altered leader peptide mutation.


ANTIMICROBIAL THERAPY

Drugs of Choice

Despite the concerning trends in antimicrobial resistance among E. coli isolates worldwide, a growing armamentarium of antimicrobial agents provides multiple options for treating E. coli infections. Ironically, these newer agents are more readily available and affordable in developed nations where E. coli resistance is less of a problem, compared to the developing world. As with other Enterobacteriaceae, where and when available, antimicrobial testing of the infecting strain should direct therapy. In other situations, knowledge of recent local susceptibility patterns is useful for guiding treatment. In general, monotherapy with trimethoprim-sulfamethoxazole, aminoglycoside, cephalosporin, or a fluoroquinolones is recommended as the treatment of choice for most known infections with E. coli, although many broad spectrum agents (such as ß-lactam/ß-lactamase inhibitor combinations and the carbapenems) remain highly active.

Treatment of infections due to multi-resistant E. coli

The presence of ESBLs and AmpC b-lactamases complicates antibiotic selection especially in patients with serious infections such as bacteraemia. The reason for this is that these bacteria are often multiresistant to various antibiotics and an interesting feature of CTX-M-producing isolates is the co-resistance to the fluoroquinolones (84). Antibiotics that are regularly used for empiric therapy of serious community-onset infections, such as the third generation cephalosporins or fluoroquinolones are often not effective against ESBL and or AmpC-producing bacteria (82). This multiple drug resistance has major implications for selection of adequate empiric therapy regimens. Empiric therapy is prescribed at the time when an infection is clinically diagnosed while awaiting the results of cultures and anti-microbial susceptibility profiles. Multiple studies in a wide range of settings, clinical syndromes, and organisms have shown that failure or delay in adequate therapy results in an adverse mortality outcome. This is also true of infections caused by ESBL-producing bacteria (92). A major challenge when selecting an empiric regimen is to choose an agent that has adequate activity against the infecting organism(s). Empirical antibiotic choices should be individualized based on institutional antibiograms that tend to be quite different from hospital to hospital, city to city and country to country.

The carbapenems are widely regarded as the drugs of choice for the empiric treatment of severe infections due to AmpC- and ESBL-producing E. coli (81). It is reasonable to suggest that ertapenem should be used for serious community-onset infections in cases where ESBL-producing isolates are suspected to be the source (80). This would include patient with the following risk factors (89) repeat UTIs, underlying renal pathology, recent administration of previous antibiotics (including cephalosporins and fluoroquinolones), previous hospitalization, nursing home residents, older males, Diabetes Mellitus, underlying liver pathology and recent international travel to high risk areas (e.g. the Indian subcontinent) (54). Imipenem or meropenem or doripenem would be more appropriate for the empiric treatment of serious hospital-onset infections in cases where ESBL-producing isolates are suspected to be the source (80). The existing data mostly from Spain suggest that piperacillin-tazobactam may be a useful agent for the treatment of some infections with ESBL-producing pathogens (88) . At the present time, however, this potential recommendation must be interpreted cautiously, because it is based on a relatively small database of information. Definitive conclusions regarding the efficacy of piperacillin-tazobactam for the treatment of infections caused by E. coli that produce ESBLs must await large-scale, prospective, randomized clinical trials.

Oral agents such as nitrofuratoin, and fosfomycin show good in-vitro activity against ESBL and AmpC-producing from different areas of the world and are adequate options for the empiric treatment of uncomplicated lower UTIs (80). However, it is important for medical practitioners to know their local susceptibility rates for nitrofuratoin against these multi-resistant bacteria, since in certain areas high resistance rates had been reported.

Other agents such as temocillin, pivmecillinam and colistin show good in-vitro activity against ESBL-producing bacteria especially if present in E. coli (99, 105). The clinical and bacteriological efficacy of pivmecillinam against lower UTIs caused by ESBL-producing E. coli and K. pneumoniae showed good clinical activity but the bacteriological cure rates were low (98). A recent study investigated the in-vitro activity of mecillinam-clavulanate combination against ESBL-producing bacteria that showed that the addition of clavulanate did improve the activity of mecillinam, even when high bacterial inoculums were present (50).

Antimicrobial options for the treatment of infections caused by E. coli that produce ESBLs, and AmpC b-lactamases are summarized in Tables 4, and 5.

Due to the very resistant nature of E. coli that produce carbapenemases, the treatment of infections due to these bacteria will remain a challenge to physicians. Clinical studies of antimicrobial therapy and the outcome of patients infected with carbapenemase-producing E. coli, compared with patients infected with susceptible strains, are very limited and suggest worse clinical outcomes for patients with infections due to resistant isolates (91). Antibiotics such as colistin, tigecycline, temocillin and fosfomycin show the best in-vitro activity against carbapenemase-producing E. coli. Unfortunately clinical evaluations have provided limited evidence for improved outcome when these agents are used (29).

Treatment of syndromes caused by E. coli

The reader is referred to those specific chapters (e.g. urinary tract infections, gastro-intestinal infections).


Current Research

One recent study is working on the adherent-invasive E. coli (AIEC) which can abnormally colonize the ileal mucosa of Crohn disease (CD) patients and adhere to and invade intestinal epithelial cells of CD patients. The study shows that this kind of CD-associated AIEC strain can adhere to the brush border of primary ileal enterocytes isolated from CD patients. The adhesion of AIEC is dependent on type 1 pili expression on baterial surface and on carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) expression on the apical surface of ileal epithelial cells. CEACAM6 is an essential receptor for AIEC strain to adhere the ileal eithelial cells in CD patients. Moreover, this study also performs in vitro experiments indicating that AIEC can boost its own colonization in CD patients.[9]

Another recent study is focusing on exploring the antigens on the outer membrane of the uropathogenic E. coli (UPEC) which can cause uncomplicated urinary tract infection (UTI), and furthermore to design a UTI vaccine to promote protective immunity against UPEC infection. In this sutdy, they apply an immunoproteomics approach to vaccine development that has been used successfully to identify vaccine targets in other pathogenic bacteria. The outer membrane proteins of UPEC from infected mice are separated by two-dimensional gel electrophoresis and are identified by mass spectrometry. A total of 23 antigens have known roles in UPEC pathogenesis, such as ChuA, IroN, IreA, Iha, IutA, and FliC. After identifying the antigens on outer membrane of UPEC, they demonstrate an antibody targeting directly on these antigens during UTI. This study shows that these conserved outer membrane antigens can be used as rational candidates for a UTI vaccine. [10]

Another recent study is focusing on genomic evolution of E. coli O157:H7 strains which diverge into two distinct lineages, lineages I and lineages II and appear to present different ecological characteristics. Lineage I strains are more commonly associated with human disease than lineage II. This experiment is carried out by microarray-based comparative genomic hybridization (CGH) to identify genomic differences among 31 E. coli O157:H7 strains which have different lineage-specific polymorphism assay types. Among 31 E. coli O157:H7 strains, there are 15 lineage I, 4 lineageI/II, and 12 lineage Ii strains, respectively. From the CGH data, they conclude that the presence of two dominant lineages subgroup E. coli O157:H7. The genomic composition of these subgroups suggests that the genomic divergence and lateral gene transfer have contributed to the evolution of E. coli. In addition, the genomic differences between lineage I and lineage II may contribute to extinct epidemiology and ecology of different strains of E. coli O157:H7. [11]

Another study involving E. coli involves the uniqueness of gram negative bacteria in the fact that they have two membranes for materials to cross in order to get in or out of the cell. The inner membrane and the outer membrane provide a barrier that is extremely proficient at maintaining homeostasis. Although the inner membrane is self-energized by proton motive force across it, the outer membrane is not self-energized, and thus must obtain energy to import and export essential substances, such as iron siderophores. Two protein systems in E. coli are known to transfer energy from the inner membrane to the outer membrane: the Ton and Tol systems. The Ton system, consisting of TonB, ExbB, and ExbD is better studied than the Tol system, consisting of TolA, TolQ, and TolR. These systems both consist of an energy harvesting complex embedded in the inner membrane of E. coli and a protein that the energy gets transferred to which in turn energizes the outer membrane. In the Ton system, ExbB and ExbD heteromultimers make up the energy harvesting complex that transfers energy to TonB, which undergoes a conformational change and provides energy for a variety of functions in the outer membrane. Similarly in the Tol system, TolQ and TolR are embedded in the inner membrane as the energy harvesting complex in heteromultimers and transfer energy to TolA, which undergoes a conformational change in order to supply energy to the outer membrane. While the Ton system has been shown to be involved with transport of materials across the membrane, the Tol system has been shown to be involved in maintenance of the outer membrane. Continued research involving these two systems could play a role in developing new antibiotics that target gram negative bacteria and their ability to facilitate the uptake of essential nutrients, as well as the extrusion of harmful substances. [13, 14, 15, 16]

A long-term study has been done on genome evolution and adaptation of Escherichia coli. Comparative genome sequencing done on an experimental population of E. coli has allowed for further investigation between the relationship between genome evolution and organismal adaptation. E. coli was grown and sampled for almost 20 years with genome sequencing at generations 2,000, 5,000, 10,000, 15,000, 20,000 and 40,000 from an asexual population that evolved with glucose as a limiting nutrient. Comparative genome sequencing showed mutational differences between the ancestral and evolved genomes accumulating in a near-linear fashion, whereas the fitness trajectory was strongly nonlinear. In particular, the rate of fitness improvement decelerated over time. The discordance in rates of genomic and adaptive evolution cannot be explained by the drift hypothesis, but rather the discrepancy may be due to clonal interference, compensatory adaptation, or changing mutation rates. In clonal interference, sub-lineages with the most beneficial mutations outcompete sub-lineages bearing mutations that are not as beneficial. Most beneficial mutations dominate the early phase of evolution for large populations in a new environment, but there are more potential mutations that confer small advantages than large (adaptative) ones. The population in the study retained a low ancestral mutation rate to at least 20,000 generations but in later generations, however, this population exhibited a greatly elevated rate of genomic evolution when a mutator lineage became established later. Furthermore, there were no synonymous mutations fixed in the first 20,000 generations and this is consistent with the low point-mutation rate in E.coli and population-genetic theory. These results indicate that it is important to explore long-term dynamic coupling between genome evolution and adaptation. [17]


Results and discussion

Process for updating the reconstruction and its content

The updated network reconstruction of E. coli K-12 MG1655 began with the iAF1260b network ( Feist et al, 2010 ), a slightly updated version of the iAF1260 network. In order to identify incorrect model predictions in order to improve the E. coli reconstruction, we experimentally determined conditional essentiality for most of the genes in the iAF1260b model. By comparing model predicted growth phenotypes to the measurements, errors in the reconstruction were found and several updates were made (Supplementary Table 1). For a discussion of the updates made to iAF1260b based on this screen, see Experimental phenotypic screens in the Supplementary Information. Next, literature and database searches were used to add newly characterized genes and reactions since 2007. The EcoCyc ( Keseler et al, 2009 ) and KEGG ( Kanehisa et al, 2010 ) databases were used extensively for this purpose. Results from the experimental screen described above also led to several model updates. After this first round of updates, the reconstruction contained 1274 genes. The network gaps ( Orth and Palsson, 2010 ) in this version of the reconstruction were then investigated using a modified version of the GapFind algorithm ( Satish Kumar et al, 2007 ). All orphan reactions (reactions without known associated genes) in the reconstruction were also identified from the model GPRs. Gaps were manually sorted into scope and knowledge gaps. Scope gaps are metabolites that are blocked in a model due to the limited scope of the network reconstruction, but have actual known producing and consuming reactions. Knowledge gaps exist because our knowledge of any metabolic network is incomplete. Targeted literature and database searches were performed for each knowledge gap to try to identify any known metabolic reactions missing from the reconstruction. We continued to add newly published metabolic information to the reconstruction during this gap-filling process, and the reconstruction was ultimately updated to iJO1366. All manual curation followed an established protocol ( Thiele and Palsson, 2010 ).

iJO1366 represents a significant expansion of the E. coli reconstruction, as it contains 1366 genes, 2251 metabolic reactions, and 1136 unique metabolites. A comparison of the content of iJO1366 and its predecessor, iAF1260, is presented in Table I. Like iAF1260, iJO1366 contains a wide range of metabolic functions (Figure 1). The complete lists of reactions and metabolites in iJO1366 can be found in Supplementary Tables 2 and 3, with a list of all references used in Supplementary Table 4. iJO1366 accounts for three cellular compartments: the cytoplasm, periplasm, and extracellular space. In total, 107 new genes were added to the reconstruction, while one gene, prpE (b0335), was removed. Most new genes added have been characterized since iAF1260 was published in 2007 (Figure 1D). The fact that some references predate previous versions of the E. coli reconstruction does not necessarily mean that they were previously missed. Rather, as genes and reactions are often added on a pathway basis, complete functional pathways are typically fully elucidated over time from multiple sources. The new genes mostly add new pathways and systems to the network, but a significant number of them fill gaps and orphan reactions in existing systems (Figure 1E). A complete list of all new and removed genes, reactions, and metabolites can be found in Supplementary Table 5. The ‘core’ and ‘wild-type’ biomass reactions of iAF1260 have also been updated in iJO1366. These are reactions that drain biomass precursor compounds in experimentally determined ratios to simulate growth ( Feist and Palsson, 2010 ). For the complete core and wild-type biomass reactions see Updating the biomass composition and growth requirements in the Supplementary Information and Supplementary Table 6. The knowledge index (number of abstracts in Medline) of the 1366 genes in the network was computed, and indicates that iJO1366 contains most of the best-characterized genes in E. coli (Knowledge index of iJO1366 genes in the Supplementary Information and Supplementary Table 7). iJO1366 was also compared with an automatically generated E. coli reconstruction from the Model SEED ( Henry et al, 2010 ) (Comparison of iJO1366 to the Model SEED E. coli reconstruction in the Supplementary Information and Supplementary Table 8) and to the protein localization database EchoLocation ( Horler et al, 2009 ) (Comparison of iJO1366 to the EchoLocation database in the Supplementary Information and Supplementary Table 9).

iJO1366 (this study) iAF1260 ( Feist et al, 2007 )
Included genes 1366 (32%) a a Overall gene coverage based on 4325 total ORFs in Escherichia coli (annotation U00096.2, downloaded from ecogene.org) 2851 of these ORFs have been experimentally verified.
1260 (29%)
Experimentally based function 1328 (97%) 1227 (97%)
Computationally predicted function 38 (3%) 33 (3%)
Unique functional proteins 1254 1148
Multigene complexes 185 167
Genes involved in complexes 483 415
Instances of isozymes b b Tabulated on a reaction basis, not including outer membrane non-specific porin transport.
380 346
Reactions 2251 2077
Metabolic reactions 1473 1387
Unique metabolic reactions c c Reactions can occur in or between multiple compartments and metabolites can be present in more than one compartment.
1424 1339
Cytoplasmic 1272 1187
Periplasmic 193 192
Extracellular 8 8
Transport reactions 778 690
Cytoplasm to periplasm 447 390
Periplasm to extracellular 329 298
Cytoplasm to extracellular 2 2
Gene–protein–reaction associations
Gene associated (metabolic/transport) 1382/706 1294/625
Spontaneous/diffusion reactions d d Diffusion reactions do not include facilitated diffusion reactions and are not included in this total if they can also be catalyzed by a gene product at a higher rate.
21/14 16/9
Total (gene associated and no association needed) 1403/720 (94%) 1310/634 (94%)
No gene association (metabolic/transport) 70/58 (6%) 77/56 (6%)
Exchange reactions 330 304
Metabolites
Unique metabolites 1136 1039
Cytoplasmic 1039 951
Periplasmic 442 418
Extracellular 324 299
  • a Overall gene coverage based on 4325 total ORFs in Escherichia coli (annotation U00096.2, downloaded from ecogene.org) 2851 of these ORFs have been experimentally verified.
  • b Tabulated on a reaction basis, not including outer membrane non-specific porin transport.
  • c Reactions can occur in or between multiple compartments and metabolites can be present in more than one compartment.
  • d Diffusion reactions do not include facilitated diffusion reactions and are not included in this total if they can also be catalyzed by a gene product at a higher rate.

A significant number of the gaps in the iAF1260 network were filled during the update to iJO1366, and several blocked pathways were unblocked. Several different types of gaps in metabolic networks are possible. Root no-production gaps are metabolites with consuming reactions but no producing reactions. Root no-consumption gaps are metabolites with producing reactions but no consuming reactions. Downstream gaps are metabolites with producing and consuming reactions but which are unable to be produced at steady state because they are downstream of a root no-production gap. Similarly, upstream gaps are upstream of root no-consumption gaps. The final reconstruction contains 48 root no-production gaps, 63 root no-consumption gaps, 52 downstream gaps, and 69 upstream gaps. In total, 11.5% of the metabolites in iJO1366 are blocked under all conditions due to gaps (Gaps and orphan reactions in the iJO1366 reconstruction in the Supplementary Information and Supplementary Table 10). The orphan reactions in models such as iJO1366 can also help to identify the functions of metabolic genes. In the original iJR904 study ( Reed et al, 2003 ), gene homology was used to predict the likely E. coli genes that encode the enzymes for 56 orphan reactions. Since then, 14 of these predictions have been independently confirmed to be correct (Supplementary Table 11), and these genes are now included in iJO1366.

Prediction of metabolic phenotypes

Flux balance analysis (FBA) ( Orth et al, 2010b ) can be used with a constraint-based model to predict metabolic flux distributions, growth rates, substrate uptake rates, and product secretion rates. The iAF1260 model and its predecessors were already very accurate at making phenotypic predictions such as growth rates and central metabolic flux distributions, so improved predictive capabilities in these areas were not expected with iJO1366. Instead, the value of the updated model is in its ability to predict phenotypes under a wider range of conditions than its predecessors.

To demonstrate the utility of the iJO1366 model in making these phenotypic predictions, we generated two large-scale sets of model phenotype predictions. First, the growth phenotypes of E. coli on all possible carbon, nitrogen, phosphorus, and sulfur sources were predicted. The numbers of growth-supporting substrates are summarized in Table II, and the full results of this screen given in Supplementary Table 12 and discussed in Prediction of all growth-supporting carbon, nitrogen, phosphorus, and sulfur sources in the Supplementary Information. We also performed a screen of model predicted growth phenotypes for all possible single gene knockout strains. Growth phenotypes were predicted on both glucose and glycerol minimal media, and the results were compared with experimental data sets (Table III Supplementary Table 13). Not unexpectedly, iJO1366 is slightly less accurate at predicting overall gene essentiality than iAF1260. This difference is due to the fact that the 107 new genes added to this model version are from less well-studied systems and pathways than the existing genes in iAF1260, as discussed more thoroughly in Prediction of gene essentiality in the Supplementary Information.

Source iJO1366 iAF1260
Potential substrates Growth supporting Potential substrates Growth supporting
Carbon 285 180 262 174
Nitrogen 178 94 163 78
Phosphorus 64 49 63 49
Sulfur 28 11 25 11
Experimental
Essential Non-essential
Growth on glucose
Computational
Essential 168 (12.3%) 39 (2.8%)
Non-essential 80 (5.9%) 1079 (79.0%)
Growth on glycerol
Computational
Essential 161 (11.8%) 45 (3.3%)
Non-essential 87 (6.4%) 1073 (78.5%)

Mapping iJO1366 to closely related strains

Although iJO1366 is a model of E. coli K-12 MG1655, gene homology mapping can be used to create models of other E. coli and Shigella strains. To date, the metabolic reconstruction of E. coli W ( Archer et al, 2011 ) is the only published reconstruction for E. coli strains other than K-12. The iJO1366 reconstruction should prove useful for the study of other recently sequenced E. coli strains. A previous analysis of multiple E. coli genomes showed that there is a moderate level of variability with respect to metabolic gene content within the species ( Vieira et al, 2011 ). This analysis went one step beyond genetic conservation, also investigating the conservation of network topology, but it stopped short of computing the capacity to carry flux through specific growth-supporting pathways.

While it is known that equivalent function is not guaranteed by gene homology, it is still one of the most commonly used and effective methods of genome annotation ( Frazer et al, 2003 ). In addition, the combination of sequence homology with constraint-based analysis of metabolic networks can be used to determine the most likely metabolic gene content of an organism by generating models that match known biology. Using this approach, we predicted with FBA whether metabolic models based on iJO1366 for 38 E. coli and Shigella strains are capable of producing biomass on glucose minimal media at various conservation thresholds (Figure 2A). At each percent identity (PID) cutoff, the set of genes that are absent from iJO1366 was determined using Smith–Waterman alignments. The set of missing genes was then used to impose constraints on metabolic reactions utilizing the iJO1366 GPRs. As expected, the results show that all strains were capable of producing biomass with no conservation requirement, but many strains lost this ability as the requirement was made more stringent. At a PID of 40%, only four strains were incapable of producing biomass. This PID was used for further analysis, and was justified through network-based analysis of auxotrophies (Figure 2B and Mapping iJO1366 to closely related strains in the Supplementary Information). Hundreds of unannotated genes in various E. coli and Shigella strains were identified through comparisons to iJO1366 genes, and are listed in Supplementary Table 14.

By analyzing the genetic content of 38 E. coli and Shigella genomes, 1006 metabolic genes in iJO1366 were found to be common to all genomes. The average genome in this analysis contains ∼97% of the genes in iJO1366 (Figure 2C). The mapping procedure described here led to the creation of 38 strain-specific models. It is important to note that these models are not yet on the same level as typical ‘draft’ metabolic models, as new metabolic functions (functions beyond those occurring in E. coli K-12 MG1655) have not yet been considered. Because only the 1366 metabolic genes of iJO1366 were considered for this mapping, the common set of genes (74%) appears larger than in the previous study by Vieira et al, which considered a set of 1545 reactions. This difference is also partly due to the fact that Vieira et al added orphan reactions to their E. coli networks and compared metabolic content on a reaction basis, rather than on a gene basis.


Additional resources

We've provided an overview of the common lab strains however, these tables are by no means exhaustive! For a more comprehensive list and additional information, visit OpenWetWare's E.coli genotype resource. Additionally, NEB has a great list of genetic markers for your reference.

Browse Addgene's curated list of Bacterial Expression Systems .

Check out our companion post describing protein expression strains, where we go over the basics of protein expression in E. coli and the common features found in those bacteria.


Watch the video: Escherichia coli with mutated z gene of lac operon cannot grow in medium containing only lact (May 2022).


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