Patent Application
20110208432
Disclosed are improved systems and methods for identifying a microorganism type in a culture.
Rapid and reliable detection of microorganisms in a culture, such as a blood culture, is among the most important functions of the clinical microbiology laboratory. Currently, the presence of biologically active agents such as bacteria in a patient's body fluid, and especially in blood, is determined using culture vials. A small quantity of the patient's body fluid is injected through an enclosing rubber septum into a sterile vial containing a culture medium and the vial is then incubated and monitored for microorganism growth.
Common visual inspection of the culture vial then involves monitoring the turbidity or observing eventual color changes of the liquid suspension within the vial. Known instrument methods can also be used to detect changes in the carbon dioxide content of the culture vessels, which is a metabolic byproduct of the bacterial growth. Monitoring the carbon dioxide content can be accomplished by methods well established in the art.
In some instances, non-invasive infrared microorganism detection instrument is used in which special vials having infrared-transmitting windows are utilized. In some instances, glass vials are transferred to an infrared spectrometer by an automated manipulator arm and measured through the glass vial. In some instances, chemical sensors are disposed inside the vial. These sensors respond to changes in the carbon dioxide concentration in the liquid phase by changing their color or by changing their fluorescence intensity. These techniques are based on light intensity measurements and require spectral filtering in the excitation and/or emission signals.
As the above indicates, several different culture systems and approaches are available to laboratories. For example, the BACTEC® radiometric and nonradiometric systems (Becton Dickenson Diagnostic Instrument Systems, Sparks, Md.) are often used for this task. The BACTEC® 9240 instrument, for example, accommodates up to 240 culture vessels and serves as an incubator, agitator, and detection system. Each vessel contains a fluorescent CO2 sensor, and the sensors are monitored on a continuous basis (e.g., every ten minutes). Cultures are recognized as positive by computer algorithms for growth detection based on an increasing rate of change as well as sustained increase in CO2 production rather than by the use of growth index threshold or delta values. The BACTEC® 9240 is completely automated once the vessels have been loaded.
A drawback with these microorganism detection approaches is that they do not always detect microorganism type in such cultures. What is needed in each of the above-identified systems is a way to non-invasively and automatically determine what type of microorganism is in a culture.
To meet the needs identified in the prior art, systems, methods, and apparatus for presumptive organism identification are provided for any culture system designed to culture a sample for the presence of microorganisms of an unknown type with an intended use of determining either the presence or the presence and identification of the microrganism type.
Advantageously, using the novel systems, methods, and apparatus of the present invention, an incubating system, such as the BACTEC® blood culture system, can be programmed to determine the microorganism type in a culture before manual tests, such as a Gram stain or a subculture, are performed. In fact, in some instances, the novel systems, methods, and apparatus of the present invention can obviate any need to perform a Gram test or a subculture in order to identify the microorganism type that is infecting a culture. Briefly, novel parameters disclosed herein, such as a maximum metabolic rate and an extent of growth, are used to determine the type of microorganisms that is infecting a culture. It has been unexpectedly discovered that each microorganism type (e.g., each microorganism species) adopts unique values for these novel parameters. Based on this unexpected discovery, the microorganism type infecting a biological sample can be determined directly by an automated incubator before manual tests, such as a Gram stain or a subculture, are performed by a lab technician. In fact, in some instances such manual tests are no longer required to determine the microorganism type infecting a culture.
In the present invention, values for the novel parameters disclosed herein from each biological sample that has been infected with a microorganism of known type are computed and used to populate an optional lookup table or to train a classifier or other form of equation that can be used to determine the identity of microorganism types. Typically, the lookup table is built using microorganisms of known species. The values of each of the microorganism types (e.g., microorganism species) that could potentially infect an unknown biological sample are computed and used to populate the lookup table. Advantageously, because the novel parameters, such as a maximum metabolic rate and an extent of growth, are computed using observables that are already recorded in conventional laboratories that work with biological samples, such a lookup table can be assembled without any requirement for running additional experiments. For example, in many laboratories, over time, several infected samples are identified using conventional Gram stains and/or subcultures. Moreover, in such laboratories, the growth curve data that tracks metabolism as a function of time has been recorded for such samples. Indeed, it is often such growth curve data that leads to the determination that such samples were infected with microorganisms. For these infected samples, the novel parameters can be computed from the growth curve data, matched with the microorganism type from the Gram stains and/or subcultures, and used to populate a lookup table. Then, the type of microorganism type infecting a new culture (an unknown) can be determined by computing the values of the novel parameters for the new culture and, for example, comparing them to the values in the lookup table for a given microorganism type.
While numerous exemplary values for the novel parameters disclosed herein are given in the data presented herein for many different microorganism types for a given media, it is to be appreciated that these values for the novel parameters for any given microorganism type may change when the media used to support growth of the culture is altered. Therefore, for any given lookup table, care should be taken to make sure that the biological media used to determine the growth curve of the unknown culture is the same or similar to the biological media used to determined the growth curve of the known samples used to populate the lookup table. Moreover, it is possible that the values of the novel parameters may vary when a different incubator is used. Thus, preferentially, the same incubator used to generate data used to populate the lookup table is also used for the unknown culture. Alternatively, several different lookup tables, where each lookup table is for a different media type and/or incubator, can be constructed.
There is disclosed herein exemplary values for the novel parameters, such as maximum metabolic rate and extent of growth, from several different microorganism types for a given growth medium. The data show that each microorganism type has a different unique and characteristic value for the novel parameters disclosed herein. Moreover, the values for the novel parameters were computed from growth data that was previously recorded for the samples and thus no additional experimentation was required to compute the values presented herein. As discussed above, the values disclosed herein for the novel parameters may shift when different media is used. However, as the data disclosed herein clearly demonstrates, for a given media, the values for the novel parameters will be different for each microorganism type and thus can be used as a basis for identifying the microorganism type in an unknown sample that has been presumptively identified as being infected with a microorganism type. As such, the systems and methods of the present invention can provide a number of applications useful in microbiology and related fields, and finds particular application in cell culture sterility test procedures. In one aspect, the present invention utilizes the differences in rate of growth and extent of growth to provide information about the microorganism type present and growing in a culture that can result in or contribute to the identification of the microorganism type. This aspect of the present invention utilizes a data transformation that can be applied to metabolic or cell growth data in a way that provides values for parameters for the microorganism type present in the culture. This aspect of the present invention can be used to determine the identity of the i microorganism type.
In another aspect, the present invention provides a method of identifying a microorganism type in a culture in a vessel. In the method, a normalization relative value is calculated for each respective measurement in a plurality of measurements of a biological state of the culture in the vessel between (i) the respective measurement and (ii) an initial biological state of the culture taken at an initial time point, thereby forming a plurality of normalization relative values.
The plurality of normalization relative values can be broken down, on a timewise basis, into predetermined fixed intervals of time points between the first time point and the second time point. For instance, a first predetermined fixed interval may include the first ten normalization relative values, a second predetermined fixed interval may include the next ten normalization relative values, and so forth until the second time point is reached. For each of these respective predetermined fixed intervals of time points between the first time point and the second time point, a first derivative of the normalization relative values in the respective predetermined fixed interval is determined, thereby forming a plurality of rate transformation values.
There is a rate transformation value for each predetermined fixed interval of time points. The plurality of rate transformation values can be considered as comprising a plurality of sets of rate transformation values. Each respective set of rate transformation values is for a different set of contiguous time points between the first time point and the second time point. For example, the first set of rate transformation values may be the first seven rate transformation values in the plurality of rate transformation values, the second set of rate transformation values may be the next seven rate transformation values in the plurality of rate transformation values, and so forth. For each respective set of rate transformation values in the plurality of sets of rate transformation values, an average relative transformation value is computed as a measure of central tendency of each of the rate transformation values in the respective set of rate transformation values. In this way, a plurality of average relative transformation values is computed.
A maximum metabolic rate and an extent of growth is determined from the plurality of normalization relative values and the plurality of average relative transformation values. In some embodiments, the maximum metabolic rate and the extent of growth is compared with an optional lookup table that matches the maximum metabolic rate and the extent of growth to a microorganism type, thereby determining the microorganism type in the culture in the vessel. In some embodiments, the maximum metabolic rate and the extent of growth is used in an equation or other form of trained classifier to determine the microorganism type in the culture in the vessel.
In some embodiments, an identification of the microorganism type in the culture in the vessel is outputted to a user interface device, a monitor, a computer-readable storage medium, a computer-readable memory, or a local or remote computer system. In some embodiments an identification of the microorganism type in the culture is displayed.
In some embodiments, the first time point is five or more minutes after the initial time point and the second time point is thirty or more hours after the initial time point. In some embodiments, the first time point is between 0.5 hours and 3 hours after the initial time point and the second time point is between 4.5 hours and twenty hours after the initial time point. In some embodiments, the measure of central tendency of the rate transformation values in a first set of rate transformation values in the plurality of sets of rate transformation values comprises a geometric mean, an arithmetic mean, a median, or a mode of each of the rate transformation values in the first set of rate transformation values.
In some embodiments, the measurements in the plurality of measurements of the biological state of the culture are each taken of the culture at a periodic time interval between the first time point and the second time point. In some embodiments, the periodic time interval is an amount of time between one minute and twenty minutes, between five minutes and fifteen minutes, or between 0.5 minutes and 120 minutes.
In some embodiments, the initial biological state of the culture is determined by a fluorescence output of a sensor that is in contact with the culture. For instance, in some embodiments, the amount of fluorescence output of the sensor is affected by CO2 concentration, O2 concentration, or pH.
In some embodiments, between 10 and 50,000 measurements, between 100 and 10,000 measurements, or between 150 and 5,000 measurements of the biological state of the culture in the vessel are in the plurality of measurements of the biological state of the culture. In some embodiments, each respective predetermined fixed interval of time points comprises or consists of each of the rate transformation values for time points in a time window between the first time point and the second time point, where the time window is a period of time that is between twenty minutes and ten hours, twenty minutes and two hours, or thirty minutes and ninety minutes.
In some embodiments, each set of rate transformation values in the plurality of rate transformation values comprises or consists of between four and twenty, between five and fifteen, or between 2 and 100 contiguous rate transformation values. In some embodiments, there are between five and five hundred or between twenty and one hundred average relative transformation values in the plurality of average relative transformation values. In some embodiments, a volume of the culture is between 1 ml and 40 ml, between 2 ml and 10 ml, less than 100 ml, or greater than 100 ml.
In some embodiments, the vessel comprises a sensor composition in fluid communication with the culture, where the sensor composition comprises a luminescent compound that exhibits a change in luminescent property, when irradiated with light containing wavelengths that cause said luminescent compound to luminesce, upon exposure to oxygen, and where the presence of the sensor composition is non-destructive to the culture and where the initial biological state of the culture is measured by the method of (i) irradiating the sensor composition with light containing wavelengths that cause the luminescent compound to luminesce and (ii) observing the luminescent light intensity from the luminescent compound while irradiating the sensor composition with the light. In some embodiments, the luminescent compound is contained within a matrix that is relatively impermeable to water and non-gaseous solutes, but which has a high permeability to oxygen. In some embodiments, the matrix comprises rubber or plastic.
In some embodiments, the maximum metabolic rate is deemed to be a maximum average relative transformation value in the plurality of average relative transformation values. In some embodiments, the extent of growth is determined by the equation:
NRafter
where NRafter
In some embodiments, the extent of growth is determined by the equation:
ARTmax*(timeARTmax−timeinitial)
where ARTmax is a maximum average relative transformation value in the plurality of average relative transformation values, timeARTmax is a duration of time between (a) the initial time point and (b) a time point when the normalization relative value in the plurality of normalization relative values that was used in the calculation of (i) the first average relative transformation value following the maximum average relative transformation value, (ii) the maximum average relative transformation value, or (iii) the first average relative transformation value preceding the maximum average relative transformation value in the plurality of average relative transformation values was measured, and timeinitial is a duration of time between (i) the initial time point and (ii) a time point when the normalization relative value in the plurality of normalization relative values that was used in the calculation of the first average relative transformation value to achieve a threshold value was measured. In some embodiments, the threshold value is a value between 5 and 100 or between 25 and 75.
In some embodiments, the extent of growth is determined by the equation:
[ARTmax*(timeARTmax−timeinitial)]/timeinitial
where ARTmax is a maximum average relative transformation value in the plurality of average relative transformation values, timeARTmax is a duration of time between (a) the initial time point and (b) a time point when the normalization relative value in the plurality of normalization relative values that was used in the calculation of (i) the first average relative transformation value following the maximum average relative transformation value, (ii) the maximum average relative transformation value, or (iii) the first average relative transformation value preceding the maximum average relative transformation value in the plurality of average relative transformation values was measured, and timeinitial is a duration of time between (i) the initial time point and (ii) a time point when the normalization relative value in the plurality of normalization relative values that was used in the calculation of the first average relative transformation value to achieve a threshold value was measured.
In some embodiments, the determining step identifies the microorganism type in the culture in the vessel as (i) a bacterium in the Enterobacteriaceae family or (ii) a bacterium not in the Enterobacteriaceae family based upon the maximum metabolic rate and the extent of growth. In some embodiments, the determining step identifies the microorganism type as bacteria based upon the maximum metabolic rate and the extent of growth. In some embodiments, the determining step identifies the microorganism type as (i) Enterobacteriaceae, (ii) Staphylococcaceae, (iii) Streptococcus, or (iv) Acinetobacter based upon the maximum metabolic rate and the extent of growth. In some embodiments, the determining step identifies the microorganism type as a single genera of the Enterobacteriaceae selected from the group consisting of Alishewanella, Alterococcus, Aquamonas, Aranicola, Arsenophonus, Azotivirga, Blochmannia, Brenneria, Buchnera, Budvicia, Buttiauxella, Cedecea, Citrobacter, Dickeya, Edwardsiella, Enterobacter, Erwinia, Escherichia, Ewingella, Griimontella, Hafnia, Klebsiella, Kluyvera, Leclercia, Leminorella, Moellerella, Morganella, Obesumbacterium, Pantoea, Pectobacterium, Candidatus Phlomobacter, Photorhabdus, Plesiomonas, Pragia, Proteus, Providencia, Rahnella, Raoultella, Salmonella, Samsonia, Serratia, Shigella, Sodalis, Tatumella, Trabulsiella, Wigglesworthia, Xenorhabdus, Yersinia, and Yokenella.
In some embodiments, the determining step identifies the microorganism type as a single species of Staphylococcaceae selected from the group consisting of Staphylococcus aureus, Staphylococcus caprae, Staphylococcus epidermidis, Staphylococcus haemolyticus, Staphylococcus hominis, Staphylococcus lugdunensis, Staphylococcus pettenkoferi, Staphylococcus saprophyticus, Staphylococcus warneri, and Staphylococcus xylosus bacteria. In some embodiments, the determining step identifies the microorganism type as a single species of Streptococcus selected from the group consisting of S. agalactiae, S. bovis, S. mutans, S. pneumoniae, S. pyogenes, S. salivarius, S. sanguinis, S. suis, Streptococcus viridans, and Streptococcus uberis.
In some embodiments, the determining step identifies the microorganism type as aerobic based upon the maximum metabolic rate and the extent of growth. In some embodiments, the determining step identifies the microorganism type as anaerobic based upon the maximum metabolic rate and the extent of growth.
In some embodiments, the initial biological state of the culture is measured by a colorimetric means, a fluorometric means, a nephelometric means, or an infrared means. IN some embodiments, each biological state in the plurality of measurements of the biological state is determined by a colorimetric means, a fluorometric means, a nephelometric means, or an infrared means. In some embodiments, the culture is a blood culture from a subject (e.g., a human subject, a mammalian subject, etc.).
In another aspect, the present invention provides an apparatus for identifying a microorganism type in a culture in a vessel in which the apparatus comprises a processor and a memory, coupled to the processor, for carrying out any of the methods disclosed herein. In still another aspect, the present invention provides is a computer-readable medium storing a computer program product for identifying a microorganism type in a culture in a vessel, where the computer program product is executable by a computer. The computer program product comprises instructions for carrying out any of the methods disclosed herein.
Yet another aspect of the present invention provides a method of identifying a microorganism type in a culture in a vessel. A plurality of measurements of the biological state of the culture in the vessel is obtained, each measurement in the plurality of measurements taken at a different time point between a first time point and a second time point. For each respective predetermined fixed interval of time points between the first time point and the second time point, a first derivative of the measurements of the biological state in the respective predetermined fixed interval of time points is determined, thereby forming a plurality of rate transformation values, where the plurality of rate transformation values comprises a plurality of sets of rate transformation values, and where each respective set of rate transformation values in the plurality of sets of rate transformation values is for a different set of contiguous time points between the first time point and the second time point. For each respective set of rate transformation values in the plurality of sets of rate transformation values, an average relative transformation value is computed as a measure of central tendency of each of the rate transformation values in the respective set of rate transformation values, thereby computing a plurality of average relative transformation values. A maximum metabolic rate and an extent of growth from the plurality of normalization relative values and the plurality of average relative transformation values is determined. The maximum metabolic rate and the extent of growth is compared with a lookup table that matches the maximum metabolic rate and the extent of growth to a microorganism type, thereby determining the microorganism type in the culture in the vessel.
Like reference numerals refer to corresponding parts throughout the several views of the drawings.
Systems, methods, and apparatus for identifying a microorganism type in a culture are provided. In one aspect, a normalization relative value is calculated for each respective measurement of a biological state of the culture between (i) the respective measurement and (ii) an initial biological state. For each fixed interval of time points, a first derivative of the normalization relative values for measurements of the biological state in the interval of time points is calculated, thereby forming a plurality of rate transformation values. For each respective set of rate transformation values in the plurality of rate transformation values, a measure of central tendency of the rate transformation values in the set is computed, thereby forming a plurality of average relative transformation values. In some embodiments, a maximum metabolic rate and an extent of growth, determined from the normalization relative values and the average relative transformation values, are compared against an optional lookup table that matches these values to a microorganism type.
The term “Acinetobacter” as used herein refers to a Gram-negative genus of bacteria belonging to the phylum Proteobacteria. Non-motile, Acinetobacter species are oxidase-negative, and occur in pairs under magnification.
The term “biological state” as used herein refers to a measure of the metabolic activity of a culture as determined by, for example, CO2 concentration, O2 concentration, pH, a rate of change in CO2 concentration, a rate of change in O2 concentration, or a rate of change in pH in the culture.
The term “blood” as used herein means either whole blood or any one, two, three, four, five, six, or seven cell types from the group of cells types consisting of red blood cells, platelets, neutrophils, eosinophils, basophils, lymphocytes, and monocytes. Blood can be from any species including, but not limited to, humans, any laboratory animal (e.g., rat, mouse, dog, chimp), or any mammal.
The term “blood culture” as used herein refers to any amount of blood that has been mixed with blood culture media. Examples of culture media include, but are not limited to, supplemented soybean casein broth, soybean casein digest, hemin, menadione, sodium bicarbonate, sodium polyaneltholesulfonate, sucrose, pyridoxal HCKl, yeast extract, and L-cysteine. One or more reagents that may be used as blood culture media are found, for example, in Stanier et al., 1986, The Microbial World, 5th edition, Prentice-Hall, Englewood Cliffs, N.J., pages 10-20, 33-37, and 190-195, which is hereby incorporated by reference herein in its entirety for such purpose. In some instances, a blood culture is obtained when a subject has symptoms of a blood infection or bacteremia. Blood is drawn from a subject and put directly into a vessel containing a nutritional broth. In some embodiments, ten milliliters of blood is needed for each vessel.
The term “culture” as used herein refers to any biological sample from a subject that is either in isolation or mixed with one or more reagents that are designed to culture cells. The biological sample from the subject can be, for example, blood, cells, a cellular extract, cerebral spinal fluid, plasma, serum, saliva, sputum, a tissue specimen, a tissue biopsy, urine, a wound secretion, a sample from an in-dwelling line catheter surface, or a stool specimen. The subject can a member of any species including, but not limited to, humans, any laboratory animal (e.g., rat, mouse, dog, chimp), or any mammal. One or more reagents that may be mixed with the biological sample are found, for example, in Stanier et al., 1986, The Microbial World, 5th edition, Prentice-Hall, Englewood Cliffs, N.J., pages 10-20, 33-37, and 190-195, which is hereby incorporated by reference herein in its entirety for such purpose. A blood culture is an example of a culture. In some embodiments, the biological sample is in liquid form and the amount of the biological sample in the culture is between 1 ml and 150 ml, between 2 ml and 100 ml, between 0.5 ml and 90 ml, between 0.5 ml and 75 ml, or between 0.25 ml and 100,000 ml. In some embodiments, the biological sample is in liquid form and is between 1 and 99 percent of the volume of the culture, between 5 and 80 percent of the volume of the culture, between 10 and 75 percent of the volume of the culture, less than 80 percent of the volume of the culture, or greater than 10 percent of the volume of the culture. In some embodiments, the biological sample is between 1 and 99 percent of the total weight of the culture, between 5 and 80 percent of the total weight of the culture, between 10 and 75 percent of the total weight of the culture, less than 80 percent of the total weight of the culture, or greater than 10 percent of the total weight of the culture.
As used herein, the term “Enterobacteriaceae” refers to a large family of bacteria, including Salmonella and Escherichia coli. Enterobacteriaceae are also referred to herein as the Enteric group. Genetic studies place them among the Proteobacteria, and they are given their own order (Enterobacteriales). Members of the Enterobacteriaceae are rod-shaped, and are typically 1 μm to 5 μm in length. Like other proteobacteria they have Gram-negative stains, and they are facultative anaerobes, fermenting sugars to produce lactic acid and various other end products. They also reduce nitrate to nitrite. Unlike most similar bacteria, Enterobacteriaceae generally lack cytochrome C oxidase, although there are exceptions (e.g. Plesiomonas). Most have many flagella, but a few genera are non-motile. They are non-spore forming, and except for Shigella dysenteriae strains they are catalase-positive. Many members of this family are a normal part of the gut flora found in the intestines of humans and other animals, while others are found in water or soil, or are parasites on a variety of different animals and plants. Most members of Enterobacteriaceae have peritrichous Type I fimbriae involved in the adhesion of the bacterial cells to their hosts. Genera of the Enterobacteriaceae include, but are not limited to, Alishewanella, Alterococcus, Aquamonas, Aranicola, Arsenophonus, Azotivirga, Blochmannia, Brenneria, Buchnera, Budvicia, Buttiauxella, Cedecea, Citrobacter, Dickeya, Edwardsiella, Enterobacter, Erwinia (e.g. Erwinia amylovora), Escherichia (e.g. Escherichia coli), Ewingella, Griimontella, Hafnia, Klebsiella (e.g. Klebsiella pneumoniae), Kluyvera, Leclercia, Leminorella, Moellerella, Morganella, Obesumbacterium, Pantoea, Pectobacterium, Candidatus Phlomobacter, Photorhabdus (e.g., Photorhabdus luminescens), Plesiomonas (e.g. Plesiomonas shigelloides), Pragia, Proteus (e.g. Proteus vulgaris), Providencia, Rahnella, Raoultella, Salmonella, Samsonia, Serratia (e.g. Serratia marcescens), Shigella, Sodalis, Tatumella, Trabulsiella, Wigglesworthia, Xenorhabdus, Yersinia (e.g., Yersinia pestis), and Yokenella. More information about Enterobacteriaceae is found in Stanier et al., 1986, The Microbial World, 5th edition, Prentice-Hall, Englewood Cliffs, N.J., Chapter 5, which is hereby incorporated by reference herein for such purpose.
As used herein, the term “instance” refers to the execution of a step in an algorithm. Some steps in an algorithm may be run several times, with each repeat of the step being referred to as an instance of the step.
As used herein, the term “microorganism” refers to organisms with a diameter of 1 mm or less excluding viruses.
As used herein, the term “microorganism type” refers to any subclassification of the bacteria kingdom such as a phylum, class, order, family, genus or species in the bacteria kingdom.
As used herein, the term “portion” refers to at least one percent, at least two percent, at least ten percent, at least twenty percent, at least thirty percent, at least fifty percent, as least seventy-five percent, at least ninety percent, or at least 99 percent of a set. Thus, in a nonlimiting example, at least a portion of a plurality of objects means at least one percent, at least two percent, at least ten percent, at least twenty percent, at least thirty percent, at least fifty percent, as least seventy-five percent, at least ninety percent, or at least 99 percent of the objects in the plurality.
As used herein, the term “Staphylococcaceae” refers to a family of bacteria in the Bacillales order that includes, but is not limited to, the Staphylococcus aureus, Staphylococcus caprae, Staphylococcus epidermidis, Staphylococcus haemolyticus, Staphylococcus hominis, Staphylococcus lugdunensis, Staphylococcus pettenkoferi, Staphylococcus saprophyticus, Staphylococcus warneri, and Staphylococcus xylosus bacteria.
As used herein, the term “Streptococcus” refers to a genus of spherical Gram-positive bacteria, belonging to the phylum Firmicutes and the lactic acid bacteria group. Cellular division occurs along a single axis in these bacteria, and thus they grow in chains or pairs, hence the name—from Greek streptos, meaning easily bent or twisted, like a chain. This is contrasted with staphylococci, which divide along multiple axes and generate grape-like clusters of cells. Species of Streptococcus include, but are not limited to S. agalactiae, S. bovis, S. mutans, S. pneumoniae, S. pyogenes, S. salivarius, S. sanguinis, S. suis, Streptococcus viridans, and Streptococcus uberis.
As used herein, a “subject” is an animal, preferably a mammal, more preferably a non-human primate, and most preferably a human. The terms “subject”, “individual” and “patient” are used interchangeably herein.
As used herein, the term “vessel” refers to any container that can hold a culture such as a blood culture. For instance, in one embodiment a vessel is a container having a side wall, a bottom wall, an open top end for receiving a culture to be contained within the container, where the container is formed from a material such as glass, clear plastic (e.g., a cyclic olefin copolymer) having a transparency sufficient to visually observe turbidity in the sample, and where the is preferably resistant to heating at a temperature of at least 250° C. In some embodiments, the container has a wall thickness sufficient to withstand an internal pressure of at least 25 psi and a closure coupled to the open end of the container, where the culture is substantially free of contamination after storage in the vessel for an extended period of time under ambient conditions. Exemplary containers are described in U.S. Pat. No. 6,432,697, which is hereby incorporated herein by reference. In some embodiments, the extended period of time under ambient conditions is at least about one year at about 40° C. In some embodiments, the vessel further comprises a fluorescent sensor compound fixed to an inner surface of the container that, when exposed to oxygen, exhibits a reduction in fluorescent intensity upon exposure to a fluorescing light. In some embodiments, the container is substantially transparent to said fluorescing light. In some embodiments, the fluorescent sensor compound comprises at least one compound selected from the group consisting of tris-4,7-diphenyl-1,10-phenanthroline ruthenium (II) salts, tris-2,2′-bipyridyl ruthenium (II) salts, 9,10-diphenyl anthracene, and mixtures thereof. In some embodiments, a vessel is a Blood Culture BACTEC®LYTIC/10 Anaerobic/F culture vial, a BBL® SEPTI-CHEK® vial, a BBL® SEPTI-CHEK® blood culture bottle, a Becton Dickinson BACTEC® vial, a Plus Aerobic/F* and Plus Anaerobic/F* culture vial, a Becton Dickinson BACTEC® Standard/10 Aerobic/F culture vial, a Becton Dickinson BACTEC® Myco/F Lytic culture vial, a Becton Dickinson BACTEC® PEDS PLUS®/F culture vial, or a Becton Dickinson BACTEC® Standard Anaerobic/F culture vial (Becton Dickinson, Franklin Lakes, N.J.).
The processor and memory illustrated in
Operation of central processing unit 22 is controlled primarily by operating system 40. Operating system 40 can be stored in system memory 36. In a typical implementation, system memory 36 also includes:
As illustrated in
Apparatus 11 determines the metabolic activity of a culture by, for example, CO2 concentration, O2 concentration, pH, a rate of change in CO2 concentration, a rate of change in O2 concentration, or a rate of change in pH in the culture. From this metabolic activity determination, apparatus 11 can identify a microorganism type in the culture. In some embodiments, apparatus 11 accommodates a number of culture vessels and serves as an incubator, agitator, and detection system. These components of apparatus 11 are not depicted in
In some embodiments, apparatus 11 is an incubator, shaker, and fluorescence detector that will hold between 1 and 1000 culture vessels (e.g., 96, 240 or 384 culture vessels). In some embodiments, the vessels are arranged in racks (e.g., circular or linear racks), each of which has a number of vessel stations. For example, in one specific embodiment, apparatus 11 will hold 240 culture vessels arranged in six racks, where each rack has 40 vessel stations. In some embodiments, each vessel station in apparatus 11 contains a light-emitting diode and a photo diode detector with appropriate excitation and emission filters (e.g., as illustrated in
Now that an exemplary apparatus in accordance with the present invention has been described, exemplary methods in accordance with the present invention will be detailed. In some embodiments, such methods can be implemented by culture type determination module 44 of
In some embodiments, an initial biological state of the blood culture is taken in step 302 using colorimetric means, fluorometric means, nephelometric means, or infrared means. Examples of colorimetric means include, but are not limited to, the use of the colorimetric redox indicators such as resazurine/methylene blue or tetrazolium chloride, or the of p-iodonitrotetrazolium violet compound as disclosed in U.S. Pat. No. 6,617,127 which is hereby incorporated by reference herein in its entirety. Another example of colorimetric means includes the colormetric assay used in Oberoi et al. 2004, “Comparison of rapid colorimetric method with conventional method in the isolation of mycobacterium tuberculosis,” Indian J Med Microbiol 22:44-46, which is hereby incorporated by reference herein in its entirety. In Oberoi et al., a MB/Bact240 system (Organon Teknika) is loaded with culture vessels. The working principle of this system is based on mycobacterial growth detection by a colorimetric sensor. If the organisms are present, CO2 is produced as the organism metabolizes the substrate glycerol. The color of the gas permeable sensor at the bottom of each culture vessel results in increase of reflectance in the unit, which is monitored by the system using infrared rays. Examples of colorimetric means further include any monitoring of the change in a sensor composition color due to a change in gas composition, such as CO2 concentration, in a vessel resulting from microorganism metabolism.
Examples of fluorometric and colorimetric means are disclosed in U.S. Pat. No. 6,096,272, which is hereby incorporated by reference herein in its entirety, which discloses an instrument system in which a rotating carousel is provided for incubation and indexing, and in which there are multiple light sources each emitting different wavelength light for colorimetric and fluorometric detection. As used herein nephelometric means refers to the measurement of culture turbidity using a nephelometer. A nephelometer is an instrument for measuring suspended particulates in a liquid or gas colloid. It does so by employing a light beam (source beam) and a light detector set to one side (usually 90°) of the source beam. Particle density is then a function of the light reflected into the detector from the particles. To some extent, how much light reflects for a given density of particles is dependent upon properties of the particles such as their shape, color, and reflectivity. Therefore, establishing a working correlation between turbidity and suspended solids (a more useful, but typically more difficult quantification of particulates) must be established independently for each situation.
As used herein, an infrared means for measuring a biological state of a blood culture is any infrared microorganism detection system or method known in the art including, but not limited to, those disclosed U.S. Pat. No. 4,889,992, as well as PCT publication number WO/2006071800, each of which is hereby incorporated by reference herein in its entirety.
In some embodiments, the vessel 202 holding the culture comprises a sensor composition 204 in fluid communication with the culture. The sensor composition 204 comprises a luminescent compound that exhibits a change in luminescent property, when irradiated with light containing wavelengths that cause the luminescent compound to luminesce, upon exposure to oxygen. The presence of the sensor composition 204 is non-destructive to the culture. In such embodiments, the measuring step 302 (and each instance of the measuring step 308) comprises irradiating the sensor composition 202 with light containing wavelengths that cause the luminescent compound to luminesce and observing the luminescent light intensity from the luminescent compound while irradiating the sensor composition with the light. In some embodiments, the luminescent compound is contained within a matrix that is relatively impermeable to water and non-gaseous solutes, but which has a high permeability to oxygen. In some embodiments, the matrix comprises rubber or plastic. More details of sensors in accordance with this embodiment of the present invention are disclosed in U.S. Pat. No. 6,900,030 which is hereby incorporated by reference herein in its entirety.
In step 304, the measured initial biological state of the culture upon initialization from step 302 is standardized and stored as the initial biological state of the culture 48 (e.g. to one hundred percent or some other predetermined value). This initial biological state, stored as data element 48 in
Apparatus 11 incubates the culture for a predetermined period of time after the initial biological state measurement is taken. Then, after the predetermined period of time has elapsed, apparatus 11 makes another measurement of the biological state of the culture. This process is illustrated by steps 306 and 308 in
In step 310 a determination is made as to whether a first predetermined fixed time interval has elapsed. For example, in some embodiments the predetermined fixed time interval is seventy minutes. In this example, if the time step t of step 306 is 10 minutes, then it would require time step t to have advanced seven times before condition 310—Yes is achieved. In some embodiments, the predetermined fixed interval of time is a duration of time that is between five minutes and five hours, a duration of time that is between twenty minutes and ten hours, a duration of time that is between twenty minutes and two hours, a duration of time that is between thirty minutes and ninety minutes, a duration of time that is less than 24 hours, or a duration of time that is more than 24 hours. When the first predetermined fixed interval of time has elapsed (310—Yes), process control passes on to step 312 where additional steps of the algorithm are performed. When the first predetermined fixed interval of time has not elapsed (310—No), process control passes back to step 306 where the algorithm waits for time to advance by the amount of time t prior to once again taking a measurement of the biological state of the culture in a new instance of step 308.
The net result of steps 306 through 310 is that a plurality of measurements of a biological state of the culture in the vessel are taken and that each measurement in the plurality of measurements is at a different time point between a first (initial) time point and a terminating (final) time point. Further, in typical embodiments where time step t is the same amount in each instance of step 306, the measurements in the plurality of measurements are each taken of the culture at a periodic interval. In some embodiments, the periodic interval is an amount of time between one minute and twenty minutes, an amount of time between five minutes and fifteen minutes, an amount of time between thirty seconds and five hours, or an amount of time that is greater than one minute.
When a predetermined fixed interval has elapsed (310—Yes), a first derivative of the normalization relative values in the respective predetermined fixed interval (or absolute values from step 302 in the respective predetermined fixed interval in embodiments in which normalization is not performed) is computed in step 312, thereby forming a rate transformation value 62. In other words, the change in the normalization relative values during the predetermined fixed interval is determined in step 312. Note that rate transformation values are the first derivative of normalization relative values in embodiments where measurement data is normalized and rate transformation values are the first derivative of absolute measurements from step 302 in embodiments where measurement data is not normalized. In some embodiments, the predetermined fixed interval of time over which the first derivative is computed is all measurements in an immediately preceding period of time that is between twenty minutes and two hours. For example, in some embodiments the predetermined fixed interval of time of step 310 is seventy minutes and, in step 312, the rate of change across all of the normalization relative values of measurements in this seventy minute time interval (the past 70 minutes) is determined in step 312 and stored as the rate transformation value 62. In some embodiments, the predetermined fixed interval of time over which the first derivative is computed (time window) is all measurements in an immediately preceding period of time that is between five minutes and twenty hours, between thirty minutes and ten hours, between twenty minutes and two hours, between twenty minutes and ten hours, or between thirty minutes and ninety minutes.
In step 314 a determination is made as to whether a predetermined number of rate transformation values have been measured since the last time condition 314—Yes was reached. If so (314—Yes), process control passes on to step 316. If not (314—No), process control returns back to step 306 where process control waits until time step t has elapsed before continuing to step 308 where the normalization relative value of the culture is once again calculated. Each condition (314—Yes) marks the completion of a set 60 of rate transformation values 62. For example, in some embodiments, condition 314—Yes is achieved when seven new rate transformation values 62 have been measured. In this example, a set 60 of rate transformation values comprises or consists of the seven rate transformation values 62. In some embodiments, each set 60 of rate transformation values 62 comprises or consists of between four and twenty contiguous rate transformation values. Contiguous rate transformation values 62 are rate transformation values in the same set 60. Such rate transformation values 62 are, for example, calculated and stored in successive instances of step 312. In some embodiments, each set 60 of rate transformation values 62 in the plurality of rate transformation values comprises or consists of between five and fifteen contiguous rate transformation values 62, between one and one hundred contiguous rate transformation values 62, between five and one fifteen contiguous rate transformation values 62, more than five rate transformation values 62, or less than ten rate transformation values 62.
When condition 314—Yes is achieved, step 316 is run. In step 316, an average relative transformation (average rate of change) value 66 is computed from the newly formed set 60 of rate transformation values 62. Thus, for each set 60 of rate transformation values 62, there is an average relative transformation value 66. In some embodiments, an average relative transformation (average rate of change) value 66 is computed from the newly formed set 60 of rate transformation values 62 by taking a measure of central tendency of the rate transformation values 62 in the newly formed set 60 of rate transformation values 62. In some embodiments, this measure of central tendency is a geometric mean, an arithmetic mean, a median, or a mode of all or a portion of the rate transformation values 62 in the newly formed set 60 of rate transformation values 62.
In step 318, a determination is made as to whether a predetermined point in the protocol has been reached. This predetermined point is a final time point, also known as an end point or second time point. In some embodiments, the second time point is reached (318—Yes) one or more hours, two or more hours, ten or more hours, between three hours and one hundred hours, or less than twenty hours after the initial measurement in step 302 was taken. In some embodiments, the second time point is reached (318—Yes) when between 10 and 50,000, between 100 and 10,000, or 150 and 5,000, more than 10, more than fifty, or more than 100 measurements of the biological state of the culture in the vessel have been made in instances of step 308. If the predetermined point in the protocol has not been reached (318—No), then process control returns to step 306 where the process control waits for time step t to advance before initiating another instance of step 308 in which the biological state of the culture is again measured and used to calculate a normalization relative value. If the predetermined point in the protocol has been reached (318—Yes), process control passes to step 320.
In step 320, the maximum metabolic rate value 57 achieved for the culture is determined. In some embodiments, the maximum metabolic rate 57 is deemed to be a maximum average relative transformation value 66 calculated in any instance of step 316 for the culture. For example, if the maximum average relative transformation value 66 ever calculated for the culture during an instance of step 316 is 250, then the maximum metabolic rate value 57 for the culture will be deemed to be 250.
In step 322, the extent of growth 58 of the culture is determined. In some embodiments, the extent of growth (EG) 58 is determined by the equation:
EG=NRafter
In some embodiments, NRafter
In some embodiments, NRafter
In some embodiments, NRafter
In some embodiments, NRafter
In some embodiments, NRafter
In some embodiments, NRminimum
In some embodiments, NRminimum
In some embodiments where Equation 1 is used to calculate extent of growth 58, the threshold value is, in nonlimiting examples, a value between 5 and 100, a value between 25 and 75, a value between 1 and 1000, or a value that is less than 50.
In some embodiments, the extent of growth (EG) 58 is determined by the equation:
EG=ARTmax*(timeARTmax−timeinitial) Eq. 2
where ARTmax is a maximum average relative transformation value 66 achieved for the culture and timeARTmax is a duration of time between (a) the initial time point when the biological state of the culture was measured in time step 302 and (b) a time point when a normalization relative value used in the calculation of (i) the first average relative transformation value following the maximum average relative transformation value, (ii) the maximum average relative transformation value, or (iii) the first average relative transformation value preceding the maximum average relative transformation value determined for the culture by instances of step 316 was measured. Further, timeinitial is a duration of time between (i) the initial time point when the biological state of the culture was measured in time step 302 and (ii) a time point when a normalization relative value, used in the calculation of the first average relative transformation value to achieve a threshold value, was measured.
In some embodiments where Equation 2 is used to calculate extent of growth 58, the threshold value is, in nonlimiting examples, a value between 5 and 100, a value between 25 and 75, a value between 1 and 1000, or a value that is less than 50.
In some embodiments, the extent of growth (EG) 58 is determined by the equation:
EG=[ARTmax*(timeARTmax−timeinitial)]/timeinitial Eq. 3
where the values for ARTmax, timeARTmax, and timeinitial are as given for Equation 2. In some embodiments where Equation 3 is used to calculate extent of growth 58, the threshold value is, in nonlimiting examples, a value between 5 and 100, a value between 25 and 75, a value between 1 and 1000, or a value that is less than 50.
The values ARTmax, timeARTmax, timeinitial, NRafter
In step 324, the maximum metabolic rate value 57 for the culture, determined in step 320, and the extent of growth 58 of the culture, determined in step 322, are used to determined the identity of the infecting microorganisms. In some embodiments of step 342, the maximum metabolic rate value 57 for the culture, determined in step 320, and the extent of growth 58 of the culture, determined in step 322, are compared with the values in lookup table 54 that matches the maximum metabolic rate 57 and the extent of growth 58 to a microorganism type 59, thereby determining the microorganism type in the culture in the vessel. To illustrate, consider the case in which the maximum metabolic rate value 57 for the culture is “200” and the extent of growth 58 of the culture is “450” and the values lookup table 54 has the following values:
In this example, the microorganism type 59 for the culture will be deemed to be type Y because the values (200, 455) in the lookup table 54 are the values that most closely match the observed values for maximum metabolic rate and extent of growth (200, 450). This example illustrates a preferred embodiment of the present invention in which the set of values 56 (maximum metabolic rate 57, extent of growth 58) in lookup table 54 that mostly closely matches the observed maximum metabolic rate 57 and extent of growth 58 for a test culture are deemed to be the matching set of values and thus the test culture is deemed to be the microorganism type 59 in the lookup table 54 that corresponds to this matching set of values. In some embodiments, a lookup table is not used. In such embodiments, the maximum metabolic rate value 57 for the culture, determined in step 320, and the extent of growth 58 of the culture, determined in step 322 are used in one or more trained classifiers or other forms of equations (e.g., regression equations) that are capable of identifying microorganism based upon maximum metabolic rate value 57 and the extent of growth 58 for the culture.
In some embodiments, step 324 identifies the microorganism type 59 in the culture in the vessel as (i) a bacterium in the Enterobacteriaceae family or (ii) a bacterium not in the Enterobacteriaceae family based upon the maximum metabolic rate 57 and the extent of growth 58 of the test culture. For instance, in some embodiments, this is done by comparing the maximum metabolic rate 57 and the extent of growth 58 of the test culture with value in the lookup table 54. In other embodiments, this is done by used the maximum metabolic rate 57 and the extent of growth 58 in one or more trained classifiers and/or other forms of equations that take into accounts values of maximum metabolic rate 57 and the extent of growth 58 of known microorganism in culture. In some embodiments, step 324 identifies the microorganism type 59 as bacteria based upon the maximum metabolic rate 57 and the extent of growth 58 of the test culture. In some embodiments, step 324 identifies the microorganism type 59 as bacteria based upon the comparing of the maximum metabolic rate 57 and the extent of growth 58 of the test culture with values in the lookup table 54. In some embodiments, step 324 identifies the microorganism type as (i) Enterobacteriacea, (ii) Staphylococcaceae, (iii) Streptococcus, or (iv) Acinetobacter based the maximum metabolic rate 56 and the extent of growth 58 of the test culture. In some embodiments, step 324 identifies the microorganism type as (i) Enterobacteriacea, (ii) Staphylococcaceae, (iii) Streptococcus, or (iv) Acinetobacter based upon comparing the maximum metabolic rate 56 and the extent of growth 58 of the test culture with values in the lookup table 54. In some embodiments, step 324 identifies the microorganism type 59 as a single genera of the Enterobacteriaceae selected from the group consisting of Alishewanella, Alterococcus, Aquamonas, Aranicola, Arsenophonus, Azotivirga, Blochmannia, Brenneria, Buchnera, Budvicia, Buttiauxella, Cedecea, Citrobacter, Dickeya, Edwardsiella, Enterobacter, Erwinia, Escherichia, Ewingella, Griimontella, Hafnia, Klebsiella, Kluyvera, Leclercia, Leminorella, Moellerella, Morganella, Obesumbacterium, Pantoea, Pectobacterium, Candidatus Phlomobacter, Photorhabdus, Plesiomonas, Pragia, Proteus, Providencia, Rahnella, Raoultella, Salmonella, Samsonia, Serratia, Shigella, Sodalis, Tatumella, Trabulsiella, Wigglesworthia, Xenorhabdus, Yersinia, and Yokenella based upon the maximum metabolic rate 56 and the extent of growth 58 of the test culture. In some embodiments, step 324 identifies the microorganism type 59 as a single genera of the Enterobacteriaceae selected from the group consisting of Alishewanella, Alterococcus, Aquamonas, Aranicola, Arsenophonus, Azotivirga, Blochmannia, Brenneria, Buchnera, Budvicia, Buttiauxella, Cedecea, Citrobacter, Dickeya, Edwardsiella, Enterobacter, Erwinia, Escherichia, Ewingella, Griimontella, Hafnia, Klebsiella, Kluyvera, Leclercia, Leminorella, Moellerella, Morganella, Obesumbacterium, Pantoea, Pectobacterium, Candidatus Phlomobacter, Photorhabdus, Plesiomonas, Pragia, Proteus, Providencia, Rahnella, Raoultella, Salmonella, Samsonia, Serratia, Shigella, Sodalis, Tatumella, Trabulsiella, Wigglesworthia, Xenorhabdus, Yersinia, and Yokenella based upon comparing the maximum metabolic rate 56 and the extent of growth 58 of the test culture with values in the lookup table 54.
In some embodiments, step 324 identifies the microorganism type 59 as a single species of Staphylococcaceae selected from the group consisting of Staphylococcus aureus, Staphylococcus caprae, Staphylococcus epidermidis, Staphylococcus haemolyticus, Staphylococcus hominis, Staphylococcus lugdunensis, Staphylococcus pettenkoferi, Staphylococcus saprophyticus, Staphylococcus warneri, and Staphylococcus xylosus bacteria. In some embodiments, the determining step identifies the microorganism type as a single species of Streptococcus selected from the group consisting of S. agalactiae, S. bovis, S. mutans, S. pneumoniae, S. pyogenes, S. salivarius, S. sanguinis, S. suis, Streptococcus viridans, and Streptococcus uberis based upon the maximum metabolic rate 56 and the extent of growth 58 of the test culture. For example, in some embodiments, the step 324 identifies the microorganism type as a single species of Streptococcus selected from the group consisting of S. agalactiae, S. bovis, S. mutans, S. pneumoniae, S. pyogenes, S. salivarius, S. sanguinis, S. suis, Streptococcus viridans, and Streptococcus uberis based upon comparing the maximum metabolic rate 56 and the extent of growth 58 of the test culture with values in the lookup table 54.
In some embodiments, step 324 identifies the microorganism type as aerobic based upon the maximum metabolic rate 56 and the extent of growth 58. In some embodiments, step 324 identifies the microorganism type 59 as anaerobic based upon the maximum metabolic rate 57 and extent of growth 58 of the test culture. In some embodiments, step 324 identifies the microorganism type as aerobic based upon comparing of the maximum metabolic rate 56 and the extent of growth 58 with values in the lookup table 54. In some embodiments, step 324 identifies the microorganism type 59 as anaerobic based upon comparing the maximum metabolic rate 57 and extent of growth 58 of the test culture with values in the lookup table 54.
In some embodiments, the method further comprises outputting an identification of microorganism type in culture 68 to a user interface device (e.g., 32), a monitor (e.g., 26), a computer-readable storage medium (e.g., 14 or 36), a computer-readable memory (e.g., 14 or 36), or a local or remote computer system. In some embodiments an identification of microorganism type in culture 68 is displayed. As used herein, the term local computer system means a computer system that is directly connected to apparatus 11. As used herein, the term remote computer system means a computer system that is connected to apparatus 11 by a network such as the Internet.
The present invention can be implemented as a computer program product that comprises a computer program mechanism embedded in a computer-readable storage medium. Further, any of the methods of the present invention can be implemented in one or more computers. Further still, any of the methods of the present invention can be implemented in one or more computer program products. Some embodiments of the present invention provide a computer program product that encodes any or all of the methods disclosed herein. Such methods can be stored on a CD-ROM, DVD, magnetic disk storage product, or any other computer-readable data or program storage product. Such methods can also be embedded in permanent storage, such as ROM, one or more programmable chips, or one or more application specific integrated circuits (ASICs). Such permanent storage can be localized in a server, 802.11 access point, 802.11 wireless bridge/station, repeater, router, mobile phone, or other electronic devices. Such methods encoded in the computer program product can also be distributed electronically, via the Internet or otherwise.
Some embodiments of the present invention provide a computer program product that contains any or all of the program modules and data structures shown in
Some embodiments of the invention may also comprise a kit to perform any of the methods described herein. In a non-limiting example, vessels, culture for a sample, additional agents, and software for performing any combination of the methods disclosed herein may be comprised in a kit. The kits will thus comprise one or more of these reagents in suitable container means.
The components of the kits, other than the software, vessels, and the radiometric or nonradiometric system, may be packaged either in aqueous media or in lyophilized form. The suitable container means of the kits will generally include at least one vial, test tube, flask, bottle, syringe or other container means, into which a component may be placed, and preferably, suitably aliquoted. Where there is more than one component in the kit, the kit also will generally contain a second, third or other additional container into which the additional components may be separately placed. However, various combinations of components may be in a vial. The kits of the present invention also will typically include a means for containing the reagent containers in close confinement for commercial sale. Such containers may include injection or blow-molded plastic containers into which the desired vials are retained.
A presumptive organism identification test has been developed for any culture system designed to culture a biological sample (hereinafter “culture”) for the presence of unknown microorganisms with the intended use of determining the presence and identification of a microorganism in the culture. The principle is a culture is inoculated into one or more culture vials, the vials are inserted into an apparatus 11 and the apparatus monitors the vials for the presence of metabolic activity (the production of carbon dioxide or other metabolites that accumulate or the consumption of substrate such as oxygen) or the accumulation of cell material (by measuring the accumulation of microbial cells). The BACTEC® blood culture system is an example of such an apparatus 11. The BACTEC® blood culture system uses fluorescent sensors that report changes to the system when microbial metabolism occurs. The algorithm depicted in
Data that was collected with the BACTEC® blood culture system is used as an example of the application of the inventive data transformation illustrated in
The inventive data transformations began with an initial normalization of the vessel signal to a specific output (its initial state upon entering the system), as described above in conjunction with steps 302 and 304 of
Examples of the parameters that were computed to determine the identity of a type of microorganism infecting a culture are presented in
The growth features that used the above-identified data transformations (rate transformation values 60, average relative transformation value 66, and the normalization relative values) for presumptive identification of microorganism type are the maximum metabolic rate and extent of growth. In this example, the maximum metabolic rate (ARTmax) was defined as the maximum ART value 66 achieved (in this example, the maximum metabolic rate was 1158).
In this example, the extent of growth (EG) was determined as
EG=NRafter
which is the difference of the normalization relative (NR) value before growth (NRminimum
Another value that was used to determine extent of growth was:
EG=ARTmax*(timeARTmax−timeinitial) Eq. 2
in which ARTmax was multiplied by the time difference (timeARTmax−timeinitial), where timeARTmax was as defined as the time to the first point following the ARTmax and was defined as the point where NR achieved a value of 50. This value for extent of growth could be used in conjunction with or instead of the extent of growth computed using equation 1. For this example, extent of growth as defined by Equation 2 had a value of 3281.
In some embodiments, the extent of growth (EG) 58 was determined by the equation:
EG=[ARTmax*(timeARTmax−timeinitial)]/timeinitial Eq. 3
where the values for ARTmax, timeARTmax, and timeinitial are as given for Equations 1 and 2. For this example, extent of growth as defined by Equation 3 had a value of 353.
Table 1 is a list of 96 clinically significant isolates that were detected in recent clinical evaluation of the BACTEC® system. The instrumented data was collected and sent to Becton Dickinson for data analysis. Table 1 contains the rate data including the key descriptor calculations mentioned above (e.g., extent of growth, maximum metabolic rate). These data are representative of microorganisms that are routinely recovered in blood. In Table 1, column 1 is a unique culture identifier, column 2 is an indication of the microorganism identified in the culture (ENTFA1 is Enterococcus faecalis, ENTCFAA is Enterococcus faecium, STRSANGR is the Streptococcus sanguinous group, STRAHE is Streptococcus alpha hemolytic, STRAGA is Streptococcus agalactiae, ESCCOL is Escherichia coli, SAUR is Staphylococcus aureus, STACNEG is Coagulase negative Staphylococcus, PROTMIR is Proteus mirabilis, KLEPNEP is Klebsiella pneumoniae, NEIMEN is Neiserria meningitidis, and ACINBAU is Acinetobacter baumanii), column 3 is an initialization time in hours, column 4 is a value for the maximum ART value achieved by the culture, column 5 is the time to achieve the maximum ART value in hours, column 6 is the time it took to reach an ART value of 50 in hours, column 7 is the time it took to reach an ART value of 20 in hours, column 8 is difference between the time it took to the maximum ART value minus the time it took to reach an ART value of 50 in hours, column 9 is the ratio between the maximum ART value and the maximum rate transformation value, column 10 is the an ARTmaxInterval50 value which is calculated as ARTmax multiplied by the time difference between (i) the time it took to achieve ARTmax and (ii) the time it took to achieve an ART value of 50, and column 11 is and ARTmaxInterval50 divided by the time it took the culture to reach an ART value of 50 in hours (the value in column 10 divided by the time it took to achieve an ART value of 50 in hours).
The next distinguishable group in
The next distinguishable group in
All references cited herein are incorporated herein by reference in their entirety and for all purposes to the same extent as if each individual publication or patent or patent application was specifically and individually indicated to be incorporated by reference in its entirety herein for all purposes.
Many modifications and variations of this invention can be made without departing from its spirit and scope, as will be apparent to those skilled in the art. The specific embodiments described herein are offered by way of example only, and the invention is to be limited only by the terms of the appended claims, along with the full scope of equivalents to which such claims are entitled.
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/US08/02173 | 2/19/2008 | WO | 00 | 5/11/2011 |
