Growth rate, transmission mode and virulence in human pathogens
Studies of the epidemiology of infectious diseases include evaluation of the .. TABLE Ranking of Infection by Infectivity, Pathogenicity, and Virulence. Severity* .. borne viral infections vary in relation to the number of mosquitoes, which. Clarification of the role of bacterial virulence factors in H. pylori pathogenesis will . Recently, the UreI channel structure has been resolved, and it may guide the . reveal the correlation between type O blood and gastric related diseases . Infection is the invasion of the host by microorganisms, which then multiply in close and the cells are pushed from the crypts to the villar tips in about 48 hours. The relationship between surface structure and virulence is important also in.
We have used a large cross-infection experiment to understand how virulence changes following a host shift. We infected 48 species of Drosophilidae with Drosophila C virus DCV and measured virulence, the change in viral load, and the transmission potential of the virus. The full host range of DCV in the wild is unknown, but it can infect other species of Drosophilidae in the laboratory [ 39 ] and can replicate when injected into other dipterans and a moth [ 40 ].
DCV causes a reduction in metabolic rate, lowers activity levels, causes intestinal obstruction, lowers the pH of the haemolymph and can ultimately result in death [ 41 — 44 ]. Here, we have investigated how the host phylogeny determines variation in virulence between species, and the relationships between virulence, viral load and the transmission potential of the virus.What is Infectivity? Explain Infectivity, Define Infectivity, Meaning of Infectivity
The DCV strain used was isolated from D. Cells were cultured at Stocks of each fly species were kept in ml bottles at staggered ages, and each day freshly eclosed flies were sexed, females were removed, and males were placed on cornmeal medium for 2 days before inoculation. The food medium used for rearing and details of the fly stocks and food recipes used can be found in Table A in S1 Text.
To inoculate flies, a 0.
These conditions were chosen as they were suitable to maintain all 48 species and carry out infection assays. As a measure of virulence we recorded mortality after infection. The number of dead flies was counted each day for 20 days and flies were transferred onto fresh medium every 3 days to minimise mortality unrelated to infection. To measure the change in viral load, half of the flies were snap frozen immediately after inoculation in liquid nitrogen as a reference sample to control for relative dose, and the rest were kept for 2 days before being snap frozen in liquid nitrogen.
The day 2 time-point was chosen based on time-course data for 10 host species Figure A in S1 Textwith viral load beginning to plateau after this time. The mortality inoculations were carried out over a period of 3 days, with the aim of completing a control and virus treatment biological replicate for each fly species each day; i. Treatment virus or control and the order in which fly species were inoculated was randomized between blocks.
- The Causes and Consequences of Changes in Virulence following Pathogen Host Shifts
- Growth rate, transmission mode and virulence in human pathogens
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The inoculations for measuring the change in viral load were carried out over 6 days, with each species being inoculated each day. Treatment frozen immediately or on day 2 post infection and the order the fly species were infected was randomized each day. In total we measured survival or the change in viral load in 12, flies. Out of the 48 species, 41 had 6 biological replicates, 2 had 5 biological replicates, 2 had 4 biological replicates and 3 had 3 biological replicates for the mortality treatments.
Out of the 48 species, 45 had 6 biological replicates and 3 had 4 biological replicates for the viral load measurements. Other factors Fly stocks were tested for Wolbachia bacterial endosymbionts using PCR primers that amplify the wsp gene [ 53 ] prior to the experiment. Wolbachia have been shown to provide resistance to DCV [ 4754 ] and so only Wolbachia-free species were used; 43 species were naturally Wolbachia free, 5 species were derived from antibiotic treated lines.
Species that had a pre-existing DCV infection were also excluded from the experiment. We also checked that the results were not affected by differences in body size between the species. Wing length is commonly used as a body size measure in Drosophila and strongly correlates with thorax length [ 5556 ]. Wings were removed from ethanol-stored flies collected at the start of the experiment, and photographed under a dissecting microscope.
The Causes and Consequences of Changes in Virulence following Pathogen Host Shifts
The length of the IV longitudinal vein from the tip of the proximal segment to where the distal segment joins vein V [ 57 ] was measured relative to a standard measurement using ImageJ software v1. We sequenced RpL32 for each species and designed specific RpL32 primers for each species in two conserved regions as described in [ 30 ]. We found the DCV primers we used amplified multiple products for D. Total RNA was extracted from Trizol homogenised flies, reverse-transcribed with Promega GoScript reverse transcriptase Promega and random hexamer primers, and then diluted 1: Two qRT-PCR reactions technical replicates were carried out per sample with both the viral and endogenous control primers.
Each qRT-PCR plate contained four standard samples, and all experimental samples were split across plates in a randomised block design. The sequences of each gene were aligned using ClustalW alignments and Genbank accession numbers for sequences used are available in an online repository http: Using ultrametric trees assumes that rates of evolutionary change virulence and viral load are proportional to time rather than proportional to the rate of sequence evolution in the genes used to construct the phylogeny.
Invasion Factors Mechanisms that enable a bacterium to invade eukaryotic cells facilitate entry at mucosal surfaces. Some of these invasive bacteria such as Rickettsia and Chlamydia species are obligate intracellular pathogens, but most are facultative intracellular pathogens Fig. The specific bacterial surface factors that mediate invasion are not known in most instances, and often, multiple gene products are involved.
Some Shigella invasion factors are encoded on a megadalton plasmid, which, when conjugated into E. Other invasion genes have also recently been identified in Salmonella and Yersinia pseudotuberculosis. The mechanisms of invasion of Rickettsia, and Chlamydia species are not well known. Capsules and Other Surface Components Bacteria have evolved numerous structural and metabolic virulence factors that enhance their survival rate in the host.
Capsule formation has long been recognized as a protective mechanism for bacteria see Ch. Encapsulated strains of many bacteria e.
Organisms that cause bacteremia e. Serum resistance may be related to the amount and composition of capsular antigens as well as to the structure of the lipopolysaccharide.
The relationship between surface structure and virulence is important also in Borrelia infections. As the bacteria encounter an increasing specific immune response from the host, the bacterial surface antigens are altered by mutation, and the progeny, which are no longer recognized by the immune response, express renewed virulence.
Salmonella typhi and some of the paratyphoid organisms carry a surface antigen, the Vi antigen, thought to enhance virulence. This antigen is composed of a polymer of galactosamine and uronic acid in 1,4-linkage. Its role in virulence has not been defined, but antibody to it is protective. Some bacteria and parasites have the ability to survive and multiply inside phagocytic cells. A classic example is Mycobacterium tuberculosis, whose survival seems to depend on the structure and composition of its cell surface.
The parasite Toxoplasma gondii has the remarkable ability to block the fusion of lysosomes with the phagocytic vacuole. The hydrolytic enzymes contained in the lysosomes are unable, therefore, to contribute to the destruction of the parasite. The mechanism s by which bacteria such as Legionella pneumophila, Brucella abortus, and Listeria monocytogenes remain unharmed inside phagocytes are not understood.
Endotoxins Endotoxin is comprised of toxic lipopolysaccharide components of the outer membrane of Gram-negative bacteria see Ch. Endotoxin exerts profound biologic effects on the host and may be lethal.
Because it is omnipresent in the environment, endotoxin must be removed from all medical supplies destined for injection or use during surgical procedures. The term endotoxin was coined in by Pfeiffer to distinguish the class of toxic substances released after lysis of bacteria from the toxic substances exotoxins secreted by bacteria.
Few, if any, other microbial products have been as extensively studied as bacterial endotoxins. Perhaps it is appropriate that a molecule with such important biologic effects on the host, and one produced by so many bacterial pathogens, should be the subject of intense investigation. Structure of Endotoxin Figure illustrates the basic structure of endotoxin.
Endotoxin is a molecular complex of lipid and polysaccharide; hence, the alternate name lipopolysaccharide. Figure Basic structure of endotoxin lipopolysaccharide from Gram-negative bacteria.
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The structure of endotoxin molecules from Salmonella spp. Enough data on endotoxin from other Gram-negative organisms have been gathered to reveal a common pattern with genus and species diversity.
Although all endotoxin molecules are similar in chemical structure and biologic activity, some diversity has evolved. Purified endotoxin appears as large aggregates. The molecular complex can be divided into three regions Fig. The polysaccharide portions are responsible for antigenic diversity, whereas the lipid A moiety confers toxicity. Dissociation of the complex has revealed that the polysaccharide is important in solubilizing the toxic lipid A component, and in the laboratory it can be replaced by carrier proteins e.
Members of the family Enterobacteriaceae exhibit O-specific chains of various lengths, whereas N. Some investigators working on the latter forms of endotoxin prefer to call them lipooligosaccharides to emphasize the chemical difference from the endotoxin of the enteric bacilli.
Nevertheless, the biologic activities of all endotoxin preparations are essentially the same, with some being more potent than others. Biologic Activity of Endotoxin The biologic effects of endotoxin have been extensively studied. Purified lipid A conjugated to bovine serum albumin and endotoxin elicit the same biologic responses. Table lists some of the biologic effects of endotoxin. The more pertinent toxic effects include pyrogenicity, leukopenia followed by leukocytosis, complement activation, depression in blood pressure, mitogenicity, induction of prostaglandin synthesis, and hypothermia.
These events can culminate in sepsis and lethal shock. However, it should be noted from Table that not all effects of endotoxin are necessarily detrimental; several induce responses potentially beneficial to the host, assuming the stimulation is not excessive.
For example, the toxicity of endotoxin is largely attributed to lipid A, attached to a polysaccharide carrier. The toxicity of lipid A is markedly reduced after hydrolysis of a phosphate group or deacylation of one or more fatty acids from the lipid A molecule.
Clinical trials are in progress to test a monophosphoryl lipid A for its potential of inducing low dose tolerance to endotoxin. Tolerance to endotoxin can be achieved by pretreatment of an animal with low doses of endotoxin or a detoxified lipid A derivative before challenge with high doses of endotoxin.
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Experimental studies have demonstrated that induction of tolerance to endotoxin reduces the dangerous effects of endotoxin. It is hoped that these relatively nontoxic lipid A derivatives may be useful in reducing the severity of bacterial sepsis in which bacterial endotoxin produces a life-threatening clinical course.
Endotoxin, which largely accumulates in the liver following injection of a sublethal dose by the intravenous route, can be devastating because of its ability to affect a variety of cell and host proteins. Kupffer cells, granulocytes, macrophages, platelets, and lymphocytes all have a cell receptor on their surface called CD14, which binds endotoxin.
Endotoxin binding to the CD14 receptor on macrophages is enhanced by interaction with a host protein made in the liver i. The extent of involvement of each cell type probably depends on the level of endotoxin exposure. The effects of endotoxin on such a wide variety of host cells result in a complex array of host responses that can culminate in the serious condition gram-negative sepsis, which often leads to shock and death.
Related to this is the matter of how to score a pathogen when its symptoms and life history vary widely across patients and infection routes: Given these limitations and to ensure our analysis was as informative as possible, we restricted our dataset to only include species for which other corresponding data were available.
To minimize variation across patients, the case fatality rates are estimates of fatality without treatment or other illnesses and represent the number of cases of a disease ending in death compared with the number of cases of the disease. We classified routes of infection used by pathogens as entry through wounded skin, inhalation or ingestion. We obtained data for case fatality rate, route of infection, facultative versus obligate parasitism, symptoms of infection and the number of pathogen cells required to start an infection infective dose by searching i databases from the United States Food and Drug Administration [ 1 ], Health Canada [ 42 ] and the Center for Disease Control and Prevention [ 43 ]; and ii direct searches in the empirical literature using keyword searches in the ISI Web of Knowledge database, Google Scholar and PubMed.
Because in vivo human infection data are unavailable and data from other host species can differ, we used in vitro generation time as a measure of parasite growth rate, with smaller generation times implying a higher growth rate. Yet, all things being equal, we expect in vitro growth rate to be correlated with in vivo growth.
In support of this, i in vitro growth measures have been shown to correlate with genomic traits associated with fast growth such as rRNA and tRNA copy number [ 44 ] and ii experimental evidence has found that in vitro and in vivo growth are correlated within species [ 4445 ]. Rate data can be modelled as a Poisson process once converted to counts per time. We, therefore, transformed generation times into number of generations per week for analytical purposes.
For interactions with the immune system, motility and quorum sensing, we first followed the electronic supplementary material of Gama et al. We have included all data and bibliographic references in electronic supplementary material, table S6. Including growth rate and infective dose as response variables, as well as case fatality rate, makes it possible to model the evolutionary change in these variables over time.
To model the effects of phylogenetic history and account for the non-independence of data arising due to common ancestry between pathogen species, we generated a phylogeny of the species in our dataset using the Structural Classification of Proteins SCOP database v. SCOP constructs phylogenetic trees on the basis of structural protein similarities derived from whole genome sequencing. Where more than one genome for a species was available in the database, we selected genomes of human isolates.
The branch lengths of phylogenies produced by SCOP represent divergence in protein structure and are non-ultrametric. Models fit in MCMCglmm require trees to be ultrametric where branch lengths provide some estimate of evolutionary time. We modelled phylogenetic history in our MR-BPMMs by fitting a variance—covariance matrix constructed from the phylogenetic tree as a random effect where the correlation in the response trait between two pathogen species is inversely proportional to time since their most recent common ancestor, assuming a Brownian model of evolution.
To assess the sensitivity of our models to branch length information, we repeated our analyses with branch lengths set arbitrarily to be equal to 1 and recovered the same qualitative results as presented in electronic supplementary material, tables S1—S5.