BACKGROUND
despite the continued progress in diagnosis and therapy of sepsis and septicemia mortality remains high.
current methods for the identification of microorganisms are based on the cultivation of the pathogens from blood with subsequent morphological and physiological characterisation  <cit> .
more than  <dig> % of all bloodstream infections are caused by only  <dig> different genera of bacteria.
staphylococci and e. coli account for more than  <dig> % of the infections  <cit> .
treatment within six hours after the first symptoms of bacteremia is crucial otherwise the infection may progress to severe sepsis.
automated blood culture systems such as bact/alert and bactec <dig> are the standard cultivation techniques in modern clinical practice.
false negative results occur periodically due to inappropriate growth conditions or antimicrobial treatment.
blood cultures without detectable microbial growth are manually subcultured, and subsequently positive results were obtained in  <dig> to  <dig> % of the cases depending on the detection method  <cit> .
conventional diagnostic methods last at least  <dig> hours due to their requirement for microbial growth rates.
in general the detection and identification is a process taking two days for most organisms or even longer for fastidious organisms  <cit> .
in contrast to this, dna-based methods meet the needs for a fast, reliable and thereby life-saving diagnosis  <cit> .
methods based on pcr amplification and subsequent hybridisation of fluorescent probes seem to be most promising approaches for early diagnosis  <cit> .
several molecular methods, including the utilisation of fluorescently labelled probes, have been tried for the detection of clinical pathogens.
fluorescent in situ hybridisation , pcr, real time pcr, single strand conformation polymorphism , and oligonucleotide microarrays have been adapted for the identification of isolated microorganisms from bacteraemia patients  <cit> .
all dna based pathogen identification methods for bloodstream infections comprise the detection of viable and dead cells as well as released microbial dna of already lysed cells.
this can lead to misinterpretation of molecular biology based detection methods on bacteria counts compared to pathogen numbers found in patients' blood using cultivation methods where e.g.
only up to  <dig> pathogens per ml blood were reported in cases of severe sepsis.
in contrast, applying quantitative rt-pcr, the density of gram positive or negative microorganisms in blood was found in a range of  <dig> to  <dig> per ml in bacteremia patients.
hackett even showed a concentration peak in severe cases of septicaemia to a maximum of  <dig>  ×  <dig> bacteria per ml  <cit> .
heininger et al.
demonstrated the advantage of pcr detection of preceding antibiotic treatment in a rat model.
whereas the detection rate of classical blood cultures falls to  <dig> % within  <dig> min after intravenous administration of cefotaxime, the pcr detection rate is still 100% at that time  <cit> .
the microarray technology has been described as a powerful tool to assess multiple parameters at the same time for various clinical scenarios such as pathogen identification of urinary tract infections , acute upper respiratory tract infections, periodontal pathogens and human intestinal bacteria.
microarrays are further applied for the analysis of microbial gene expression and diversity  <cit> .
in this study a dna microarray-based assay is presented which allows the identification of  <dig> different bloodstream infection relevant pathogens  from whole blood samples.
the array represents a further contribution towards a possible implementation of dna chips in clinical diagnostics.
the complete analysis can be done within  <dig> hours in a research laboratory starting with pathogen isolation from artificially-spiked blood to species identification.
such a rapid diagnostic test could support decisions for antibiotic treatments due to accurate discrimination of closely related species.
RESULTS
probe and array design
bacterial 16s rrna sequences and 18s rrna sequences of candida sp.
were imported into the arb software database and aligned to sequences present in the database.
a phylogenetic tree of all species which can be identified with the newly developed microarray was calculated using the neighbour joining method.
all in all  <dig> different dna probes were designed using the arb software package.
additional probes were downloaded from the probebase website  <cit> .
more than  <dig> different probes were applied and separately evaluated in this study and  <dig> probes were further kept for the final set up .
the other ones were removed because of cross hybridisations or insufficiently specific signal responses.
the hybridisation behaviour was found to be difficult to predict but calculating binding capacities by consideration of weighted mismatches still gives a very precise idea about overall species identification patterns .
however, different probes for identification of the same species still performed differently although they had equal in silico predicted behaviour, similar positions on the marker gene, similar g+c contents, lengths and melting temperatures .
list of probes used in this study including their nucleotide sequences and some characteristics.
abbreviations: ab: acinetobacter, cb: citrobacter, eb: enterobacter, ec: enterococcus, e: escherichia, k: klebsiella, m: morganella, p: proteus, pm: pseudomonas, sr: serratia, sm: stenotrophomonas, s: streptococcus, sta: staphylococcus, c: candida
weights for mismatches related to their position in the sequence.
a single mismatch at the first position of the probe is weighted with  <dig>  whereas mismatches at central positions of the probes were weighted highest with  <dig> .
these values were experimentally determined.
weights of mismatches due to the type of mismatched bases.
a mismatch of adenine on the probe with cytosine on the target sequence is weighted with  <dig> , whereas a mismatch of the same probe with a guanine in the target sequence is weighted with  <dig> .
to determine optimal probe quantities on the microarray different probe concentrations  were printed in a defined buffer.
probe concentrations of  <dig> μm gave highest signals.
probe concentrations above  <dig> μm were not tested since they were already found in other microarray applications not to lead to further signal increase.
specificity
an in silico hybridisation matrix was generated with the probe match function in the arb software package and the calcoligo software.
the modelled hybridisation behaviour of each probe was in good agreement with real experimental data .
cross hybridisation within the enterobacteriaceae family was already predicted by in silico calculations due to highly conserved 16s rrna sequences and confirmed by experimental results.
the calculated matrix showed similar hybridisation patterns as achieved through hybridisation assays .
due to the application of short oligonucleotide probes it was possible to discriminate sequences differing from each other by a single nucleotide.
this was demonstrated using probe ecl  <dig>  that matches perfectly with the species e. cloacae and k. oxytoca generating average signal intensities of  <dig>   <dig> respectively.
in contrast, hybridising amplified 16s rdna of the species e. aerogenes and k. pneumoniae resulted in no detectable signal because of a nucleotide change at e. coli position  <dig> .
this mismatch was only weighted with  <dig>  applying the parameters described in table  <dig> and  <dig>
normalised signal values of  <dig> hybridisation experiments are summarised in fig  <dig> and also supplied as table .
the observed hybridisation values showed low coefficient of variation  among the  <dig> replicate spots and between the different assays.
the cv of all specific signals ranged from  <dig>  % to  <dig>  % for  <dig> % of the probes.
high cv values resulted from experiments done at or just above the detection limit yielding only faint signals .
since in clinical routine the possibility of little initial bacterial quantities is rather high reliable result interpretation must be guaranteed even at low bacterial loads.
this represents a limitation of short oligonucleotide microarrays since they are at risk to lead to a misinterpretation of results below or also near the detection limit.
species that were not used at the detection limit, such as s. marcescens or s. maltophilia, gave lower cv values ranging from  <dig> % to  <dig> %.
as expected from calcoligo analysis, cross-hybridisations of individual probes occurred within the enterobacteriaceae family especially in the group of klebsiella-enterobacter-citrobacter.
however, specific signal patterns could be assigned to each species enabling the identification of cultures at species level.
for acinetobacter and proteus reliable identification is only guaranteed at genus level which is sufficient for most clinical applications.
sensitivity
limits of bacterial detection  were assessed with spiked blood samples and pure cultures using dilution series from  <dig> to  <dig> bacteria per ml from selected gram positive and gram negative bacterial species.
the detection limit in pure cultures was lower than in spiked blood due to pcr interference of blood components.
pcrs carried out from pure cultures were found to amplify dna down to  <dig> cells per assay resulting in a clearly visible band on a  <dig> % agarose gel.
identification based on microarrays was  <dig> times more sensitive than the agarose gel evaluation demonstrated.
specific and reproducible signals down to  <dig> bacteria per assay could be achieved for e. coli.
analysis of staphylococcal cultures revealed the highest detection limit within the group of gram positive bacteria with about  <dig> cells necessary per assay to see signals on the microarray .
sensitivity studies were carried out with other gram negative and positive species and found to be similar to those mentioned before.
c. freundii and k. pneumoniae had a detection limit of  <dig> bacteria per assay whereas e. faecalis and s. epidermidis were detectable only at  <dig> cells per assay.
this difference in sensitivity can be ascribed to less efficient cell lysis due to the presence of a persistent cell wall and the presence of a thermostable dnase in the staphylococcal proteome  <cit> .
the adaptation of the protocol to different cell lysis steps or an additional enzymatic treatment can certainly further improve the detection limit.
parallel detection of pathogens
the densities of bacterial suspensions were adjusted as described in materials and methods and equal amounts were added to single species and double species experiments.
the hybridisation results of combinations of different strains were compared to those of single strains.
the multiple microbial assays produced a signal pattern that matched the compounded signals of single species hybridisations .
due to these results a clear differentiation of species in a multiple microbial infection is possible.
some experiments were carried out based on spiked blood confirming the results of pure cultures .
parallel detection showed that most probes generated weaker signal intensities when two pathogens were present in one sample.
this fact would lead to a lower sensitivity when polymicrobial samples are handled which enhances the risk of false result interpretation near the detection limit.
hybridisation of blood sample isolates
starting from bacterial dna isolated from blood pcr and labelling protocols were optimised with respect to reducing interference of blood components.
addition of glycerol and betaine reduced non-specific amplification during the pcr and labelling steps in spite of large amounts of residual human dna.
by this means the yield of specific pcr product was also clearly increased resulting in equal specificities as with cultured microbes.
no cross-hybridisation provoked by human dna was observed .
similar results were obtained when detecting combinations of single microbes simulating multiple microbial infections as already described above.
the obtained signal patterns were as specific for the added strains as those from single species microarray hybridisations .
the sensitivity of the method was determined by providing a ten-fold dilution series in  <dig> ml spiked blood.
detection limit was found to be as low as  <dig> bacteria per ml whole blood.
however, as observed with pure cultures the sensitivity of gram positive bacteria is much lower, e.g.
<dig> per ml blood for s. aureus.
normalisation
normalisation is an important aspect of all microarray experiments.
usually it requires a set of probes which are expected to give a constant signal throughout all hybridisations.
in the present application there are no endogenous genes or sequences to suit this requirement.
therefore the only other option would be to spike known amounts of sequences similar to the 16s rrna gene into bacterial suspension before cell lysis or directly into the dna extract.
however, spike controls are known to be potentially unreliable due to inaccuracies in nucleic acid quantitation and pipetting errors.
also, there could be competitive effects between the spike oligonucleotide and the target 16s gene during pcr, thus introducing a bias.
therefore a quantile normalisation approach was chosen, based on the assumption that each array should have a number of probes which give a positive signal  and the rest of the probes a low  signal.
this algorithm is a between-array normalisation approach which shifts the signal density of each hybridisation towards an average density across all hybridisations  <cit> .
classification
fig  <dig> shows the clear clusters of hybridisations as well as of probes.
although each probe was designed to bind to one specific pathogen, the heatmap shows that some probes are very specific to one species while others yield signals for a wider range of different organisms and a few probes do not show any specific signal at all.
a classical approach would be to evaluate each probe set across all hybridisations and define a signal threshold e.g.
by roc analysis  <cit>  to distinguish positive from negative signals.
however, since some probes show cross-hybridisation between species or even genera, this would not only lead to problems with specificity, but would also mean a loss of information contained in the cross-hybridisation patterns.
a machine learning approach was used to classify a hybridisation pattern by similarity to hybridisations with known organisms.
the k-nearest neighbour  method was used and validated in a leave-one-out cross-validation approach.
at genus level, all  <dig> hybridisations were classified correctly and  <dig> % at species level.
in  <dig> cases the species p. mirabilis and p. vulgaris and in  <dig> cases a. baumannii and a. radioresistens were confounded.
these misclassifications are not surprising, taking into account the high sequence similarity between the respective organisms.
possibly some of the misclassifications are due to low numbers of hybridisations in the test set, and could be avoided by adding more experiments to the test set.
discussion
the present microarray for the identification of blood isolates is so far the first microarray-based molecular diagnostic tool to identify a wide range of clinically relevant bacteria and yeast directly from blood in an appreciated period of time.
another similar approach applying isolates of positive blood cultures has been published previously  <cit> .
the authors of this article introduce 19-mer 16s rdna signature oligonucleotides which were spotted on ta2o5- coated microarrays in order to allow evanescent-waveguide readout.
hybridisation data were analysed using hierarchical clustering analysis and pattern recognition appyling a decision tree.
the combination of pcr amplification with microarray hybridisation represents a powerful tool for pathogen identification.
it exceeds conventional technologies in speed while performing at an extremely high specificity.
analysis of 16s rrna genes has been reported before to allow a more robust, reproducible, and accurate testing than phenotypic methods  <cit> .
over  <dig> sequences have been analyzed in the arb software package to design species- and genus-specific microarray probes and calculate the hybridisation behaviour of these probes to target dna from the respective bacterial species.
predicted and experimental values showed strong correlation.
short oligonucleotide probes ranging between  <dig> and  <dig> mer were used for this study because they allow distinct discrimination of single nucleotide differences under stringent conditions.
their hybridisation properties are fundamentally different compared to long oligonucleotide probes which usually have a length of  <dig> to  <dig> mer thus showing higher binding capacities and thereby leading to higher detection sensitivities on a microarray.
however, the threshold of differentiation of long oligonucleotide probes is at best  <dig> % sequence similarity, which makes them not suitable for species identification based on the 16s rrna marker gene.
other marker genes were considered as potential targets for probe design especially some genes already known for their elevated sequence variability that might allow better discrimination of members of the family enterobacteriaceae.
however, an eminent advantage of the 16s marker gene is its good characterisation and the online availability of thousands of sequences.
furthermore in the meantime there is an arb databank for free downloading on the homepage of the technical university munich which contains more than  <dig> complete and aligned 16s rrna sequences including phylogenetic relations calculated by the neighbour joining method.
additional sequences can be downloaded from any online database or manually added to the arb database.
this way the accession to  <dig>  <dig> sequences of 16s rrna genes is possible through the ribosomal database project ii  .
with our approach we showed that this marker gene is well suited to discriminate even very closely related species.
it was further demonstrated that analysis based on ribosomal rna can be performed in presence of a strong background of human dna.
taking all the considerations into account there still remain two possible approaches for probe design.
first the use of long oligonucleotide probes which allows high sensitivity.
however, for equal specificity the application of several marker genes would be necessary to identify the whole panel of microbes.
such an approach necessitates the realisation of a multiplex pcr that might attenuate benefits in sensitivity of long probes.
further distinct species discrimination within the family enterobacteriaceae would still be difficult.
on the other hand the employment of short probes targeting solely the 16s rrna gene also allows good discrimination and even species identification by pattern recognition within very closely related species.
applying stringent conditions this approach even allows detection of single nucleotide differences .
furthermore the use of the most characterised marker gene with the highest number of available sequences allows reliable in silico predictions based on experimentally obtained data.
standard clinical identification procedures require  <dig> days and up to  <dig> days for microorganisms that are difficult to cultivate.
in contrast to cultivation- and bacterial enrichment dependent methods microarrays enable not only a fast and accurate but also highly parallel identification of different microorganisms in one assay.
the present protocol can be carried out within  <dig> hours from drawing blood to the presentation of results by an analysis software, when gel electrophoresis for pcr product confirmation and pre-hybridisation are carried out in parallel with labelling reaction.
most identifications were realised analysing  <dig> different samples and  <dig> positive as well as  <dig> negative control.
therefore  <dig> samples had to be proceeded in parallel.
the dna preparation lasted  <dig>  hours, the amplification reaction  <dig>  hours, the labelling  <dig> min, the hybridisation  <dig> hour, the washing  <dig> minutes and the scanning also  <dig> minutes.
the applied mastermixes and buffers were prepared prior to the analysis in large amounts so that each solution was ready to use.
thus diagnosis can be obtained within a working day when blood is collected from the patient in the morning.
the current assay time of  <dig> hours can be easily reduced by  <dig> hours using meanwhile commercially available fast pcr devices .
online fluorescence scanner or electrode chip based systems could be applied for faster assay performance.
a further reduction in assay time can be achieved when dna isolation from blood is done as an automated and integrated process.
such systems are currently being tested in the clinical practice.
the shorter duration would allow the realisation of several detection runs per day.
additionally, the handling steps would thus be reduced thereby reducing the danger of infection for personnel performing the assay.
furthermore compared to cultivation-based identification procedures dna based methods have the advantage to enable even the detection of static or dead cells before genome degradation e.g.
in the case of administration of antibiotics when no further growth in culture can be observed  <cit> .
however dna-based detection methods are not able to distinguish between alive and dead cells which might lead to misguiding therapeutic conclusions since initial antibiotic treatments are always applied prior to first blood withdrawal.
in the case of multiple infections, where one species is already eradicated by antibiotics, the other species could be underestimated due to a high amount of dna from the non-viable bacteria.
most studies on nucleic-acid based identification of blood-borne pathogens, including multiplex-pcr, real-time pcr and microarrays, were so far restricted to blood cultures and mostly to the identification of selected members of the enterobacteriaceae family or gram positive bacteria like staphylococcus and streptococcus  <cit> .
the application of microarrays for pathogen identification of clinical specimens has already been proposed earlier.
amongst published tools are arrays for upper respiratory tract infections, urinary tract infections, human faeces analysis and blood stream infections.
microbial detection has been achieved applying different marker genes because of known inconvenience of 16s rrna due to high sequence similarities between closely related species.
the suitability of 23s rrna, the topoisomerases gyrb and pare has been proven for distinct species discrimination  <cit>  the small and large subunit rrna genes, virulence factors and antibiotic resistance determinants have been successfully applied as markers for the detection of bloodstream infections  <cit> .
however, all microarray based studies were carried out so far with clinical specimens isolated from blood culture that partially neutralises the main advantage of identification by molecular methods.
on the other hand direct detection from whole blood samples implicates higher detection limits.
a general limitation of microbial detection microarrays compared to blood cultures is the generation of false negative results for species with no specific probe within the panel.
this study was carried out with whole blood and it was shown that no cross-hybridisation is caused by human background dna .
the developed probe panel further covers the species most frequently associated with bloodstream infections and can easily be extended.
the applied normalisation has the advantage that no more control is needed for correct classification of the outcomes.
each result can be added to the classifier leading to even more precise calculations.
the present pathogen identification microarray is to our knowledge the first microarray assay for the parallel identification of a total of  <dig> blood-born bacterial species as well as  <dig> clinical relevant candida species which enables pathogen identification down to  <dig> cfu/ml blood without any preculturing.
using this microarray for pure cultures detection limits in the range of  <dig> and  <dig> bacteria per assay were achieved, whereas the limit of detection for bacteria in spiked blood was found to be  <dig> to  <dig> bacteria per ml blood depending on the targeted microbes.
since even in blood of severe sepsis patients only  <dig> viable pathogenic cells per ml blood can be found this high detection limit is a clear shortcoming of this method implicating false negative results or the risk of detection of mostly dead cells thus leading to misguidance.
the higher lod of spiked blood samples compared to pure cultures results from pcr inhibitory components in blood  <cit> .
additional dna purification can reduce the amount of these inhibitors, but high levels of residual human dna still render lower lod difficult.
due to high sequence similarities of the 16s rrna gene short oligonucleotide probes were used in order to increase specificity.
however, such an improvement implicates a reduction of sensitivity which also leads to strong signal variations near the limit of detection.
in our study this problem could be overcome by microarray result evaluation by the developed pattern recognition which quantities and normalises signal strengths.
but in routine application this fact would display a high risk of result misinterpretation near the detection limit.
different approaches to increase signal intensity and to further reduce the lod of microarray analysis may be applied to this test.
one possibility is the usage of a rotating microchamber for supporting the stirring of the hybridisation mix  <cit> .
other improvement strategies concern the choice of probes for detecting pathogens.
this includes the introduction of poly-t spacers to dna probes to avoid steric hindrance during hybridisation, investigating different lengths of probes or enlarge the probe selection to several thousands in order to produce specific patterns and to cover a wide range of identifiable organisms  <cit> .
the presented pathogen microarray includes  <dig> dna probes with an average length of 20– <dig> bp, all derived from the prokaryotic and eukaryotic small-subunit ribosomal rna gene.
due to high sequence similarities in the 16s rrna gene especially among members of the enterobacteriaceae group, it was evident that not all designed dna probes would give 100% species-specific signals on the microarray.
however, we could overcome this problem by taking advantage of the species-specific patterns of signals obtained after microarray hybridisation.
applying a supervised k-nearest neighbour  classification method all of the tested bacteria and yeasts were identified correctly at the genus level and  <dig>  % at the species level.
high 16s rdna sequence similarity caused only misclassification in case of p. mirabilis and vulgaris and a. radioresistens and baumanii, respectively.
based on this microarray  <dig> different microbes of bloodstream infections are identifiable.
however this panel may be expanded by further organisms as new pathogens appear in clinical routine and slight variants are observed when organisms are isolated from clinical specimens in different regions  <cit> .
further microorganisms could be staphylococcus lugdunensis, streptococci like s. agalactiae, salmonella spp., aeromonas spp.
or candida krusei which could be easily included in the current microarray by designing species- and genus specific probes for them.
a database was established serving as a classifier for the applied statistical method.
this analysis method includes pattern recognition and machine learning algorithms.
the chosen algorithm k-nearest-neighbour method executes an accurate identification within a fully automated platform.
moreover a software package is under development which includes the flexibility of subsequent addition of single probes, individual species, groups of species or even an exchange of the whole classifier.
a possible enlargement of the classifier by addition of further hybridisation results increases the specificity of identification, by reducing misinterpretation possibility due to false negative signals or cross hybridisations .
such a software allows automatic processing of microarray image files and will retrieve genus and species level identification.
additionally, recommendations of appropriate antibiotic treatments can be given from the statistical assessment of periodically updated information on antibiotic resistances.
however, such guidance only relies on past data of statistical records.
the most appropriate assistance would be gained based on antibiotic resistance determination by detection of the genetic determinants.
such information can only be obtained by the realisation of multiplex pcr which would further reduce the sensitivity of the method.
since seven percent of all bloodstream infections are polymicrobial  <cit> , the probe pattern and the classification algorithm were also tested for randomly selected dual bacterial combinations.
signal patterns from multiple microorganisms detection could be predicted from single microbe signals.
in each case both pathogens present in the sample could be correctly identified.
negative controls of unspiked blood gave negative pcr amplification and hybridisation results.
this confirms the absence of bacteria or bacterial dna in the blood of healthy humans  <cit> .
the combination of microbial identification with clinical antibiotic resistance determination reveals a considerable potential.
dna microarrays have already been adopted for detection of quinolone-resistant e. coli or for the genotyping of tem beta-lactamases  <cit> .
an antibiotic resistance microarray specifically targeted to blood-born pathogens is under development in our group following the successful establishment of a first prototype array.
CONCLUSIONS
in this study we have developed a rapid and sensitive method for dna based identification of clinically relevant pathogens that cause bloodstream infections.
the microarray method has been shown to detect and identify pathogens down to concentrations of  <dig> bacteria per ml within  <dig> hours.
relying on the analysis of signal patterns the assay specificity was determined to be  <dig> % at genus level and more than  <dig>  % at species level.
however, depending on clinical specimen the isolation protocol must be adapted in order to optimise microbial dna yield and to assure maximum safety to operating personnel.
but the work also shows that a microarray based on the 16s rrna marker gene is a potentially powerful identification tool for routine clinical laboratory diagnostics.
additionally the range of identifiable organisms can easily be extended to new pathogens and also multimicrobial infections can be considered.

 despite the continued progress in diagnosis and therapy of sepsis and septicemia mortality remains high. current methods for the identification of microorganisms are based on the cultivation of the pathogens from blood with subsequent morphological and physiological characterisation. more than % of all bloodstream infections are caused by only different genera of bacteria. staphylococci and e. coli account for more than % of the infections. treatment within six hours after the first symptoms of bacteremia is crucial otherwise the infection may progress to severe sepsis. automated blood culture systems such as bact/alert and bactec are the standard cultivation techniques in modern clinical practice. false negative results occur periodically due to inappropriate growth conditions or antimicrobial treatment. blood cultures without detectable microbial growth are manually subcultured, and subsequently positive results were obtained in to % of the cases depending on the detection method. conventional diagnostic methods last at least hours due to their requirement for microbial growth rates. in general the detection and identification is a process taking two days for most organisms or even longer for fastidious organisms. in contrast to this, dna-based methods meet the needs for a fast, reliable and thereby life-saving diagnosis. methods based on pcr amplification and subsequent hybridisation of fluorescent probes seem to be most promising approaches for early diagnosis. several molecular methods, including the utilisation of fluorescently labelled probes, have been tried for the detection of clinical pathogens. fluorescent in situ hybridisation, pcr, real time pcr, single strand conformation polymorphism, and oligonucleotide microarrays have been adapted for the identification of isolated microorganisms from bacteraemia patients. all dna based pathogen identification methods for bloodstream infections comprise the detection of viable and dead cells as well as released microbial dna of already lysed cells. this can lead to misinterpretation of molecular biology based detection methods on bacteria counts compared to pathogen numbers found in patients' blood using cultivation methods where e.g. only up to pathogens per ml blood were reported in cases of severe sepsis. in contrast, applying quantitative rt-pcr, the density of gram positive or negative microorganisms in blood was found in a range of to per ml in bacteremia patients. hackett even showed a concentration peak in severe cases of septicaemia to a maximum of × bacteria per ml. heininger et al. demonstrated the advantage of pcr detection of preceding antibiotic treatment in a rat model. whereas the detection rate of classical blood cultures falls to % within min after intravenous administration of cefotaxime, the pcr detection rate is still 100% at that time. the microarray technology has been described as a powerful tool to assess multiple parameters at the same time for various clinical scenarios such as pathogen identification of urinary tract infections, acute upper respiratory tract infections, periodontal pathogens and human intestinal bacteria. microarrays are further applied for the analysis of microbial gene expression and diversity. in this study a dna microarray-based assay is presented which allows the identification of different bloodstream infection relevant pathogens from whole blood samples. the array represents a further contribution towards a possible implementation of dna chips in clinical diagnostics. the complete analysis can be done within hours in a research laboratory starting with pathogen isolation from artificially-spiked blood to species identification. such a rapid diagnostic test could support decisions for antibiotic treatments due to accurate discrimination of closely related species.  probe and array design bacterial 16s rrna sequences and 18s rrna sequences of candida sp. were imported into the arb software database and aligned to sequences present in the database. a phylogenetic tree of all species which can be identified with the newly developed microarray was calculated using the neighbour joining method. all in all different dna probes were designed using the arb software package. additional probes were downloaded from the probebase website. more than different probes were applied and separately evaluated in this study and probes were further kept for the final set up. the other ones were removed because of cross hybridisations or insufficiently specific signal responses. the hybridisation behaviour was found to be difficult to predict but calculating binding capacities by consideration of weighted mismatches still gives a very precise idea about overall species identification patterns. however, different probes for identification of the same species still performed differently although they had equal in silico predicted behaviour, similar positions on the marker gene, similar g+c contents, lengths and melting temperatures. list of probes used in this study including their nucleotide sequences and some characteristics. abbreviations: ab: acinetobacter, cb: citrobacter, eb: enterobacter, ec: enterococcus, e: escherichia, k: klebsiella, m: morganella, p: proteus, pm: pseudomonas, sr: serratia, sm: stenotrophomonas, s: streptococcus, sta: staphylococcus, c: candida weights for mismatches related to their position in the sequence. a single mismatch at the first position of the probe is weighted with whereas mismatches at central positions of the probes were weighted highest with. these values were experimentally determined. weights of mismatches due to the type of mismatched bases. a mismatch of adenine on the probe with cytosine on the target sequence is weighted with, whereas a mismatch of the same probe with a guanine in the target sequence is weighted with. to determine optimal probe quantities on the microarray different probe concentrations were printed in a defined buffer. probe concentrations of μm gave highest signals. probe concentrations above μm were not tested since they were already found in other microarray applications not to lead to further signal increase. specificity an in silico hybridisation matrix was generated with the probe match function in the arb software package and the calcoligo software. the modelled hybridisation behaviour of each probe was in good agreement with real experimental data. cross hybridisation within the enterobacteriaceae family was already predicted by in silico calculations due to highly conserved 16s rrna sequences and confirmed by experimental results. the calculated matrix showed similar hybridisation patterns as achieved through hybridisation assays. due to the application of short oligonucleotide probes it was possible to discriminate sequences differing from each other by a single nucleotide. this was demonstrated using probe ecl that matches perfectly with the species e. cloacae and k. oxytoca generating average signal intensities of respectively. in contrast, hybridising amplified 16s rdna of the species e. aerogenes and k. pneumoniae resulted in no detectable signal because of a nucleotide change at e. coli position. this mismatch was only weighted with applying the parameters described in table and normalised signal values of hybridisation experiments are summarised in fig and also supplied as table. the observed hybridisation values showed low coefficient of variation among the replicate spots and between the different assays. the cv of all specific signals ranged from % to % for % of the probes. high cv values resulted from experiments done at or just above the detection limit yielding only faint signals. since in clinical routine the possibility of little initial bacterial quantities is rather high reliable result interpretation must be guaranteed even at low bacterial loads. this represents a limitation of short oligonucleotide microarrays since they are at risk to lead to a misinterpretation of results below or also near the detection limit. species that were not used at the detection limit, such as s. marcescens or s. maltophilia, gave lower cv values ranging from % to %. as expected from calcoligo analysis, cross-hybridisations of individual probes occurred within the enterobacteriaceae family especially in the group of klebsiella-enterobacter-citrobacter. however, specific signal patterns could be assigned to each species enabling the identification of cultures at species level. for acinetobacter and proteus reliable identification is only guaranteed at genus level which is sufficient for most clinical applications. sensitivity limits of bacterial detection were assessed with spiked blood samples and pure cultures using dilution series from to bacteria per ml from selected gram positive and gram negative bacterial species. the detection limit in pure cultures was lower than in spiked blood due to pcr interference of blood components. pcrs carried out from pure cultures were found to amplify dna down to cells per assay resulting in a clearly visible band on a % agarose gel. identification based on microarrays was times more sensitive than the agarose gel evaluation demonstrated. specific and reproducible signals down to bacteria per assay could be achieved for e. coli. analysis of staphylococcal cultures revealed the highest detection limit within the group of gram positive bacteria with about cells necessary per assay to see signals on the microarray. sensitivity studies were carried out with other gram negative and positive species and found to be similar to those mentioned before. c. freundii and k. pneumoniae had a detection limit of bacteria per assay whereas e. faecalis and s. epidermidis were detectable only at cells per assay. this difference in sensitivity can be ascribed to less efficient cell lysis due to the presence of a persistent cell wall and the presence of a thermostable dnase in the staphylococcal proteome. the adaptation of the protocol to different cell lysis steps or an additional enzymatic treatment can certainly further improve the detection limit. parallel detection of pathogens the densities of bacterial suspensions were adjusted as described in materials and methods and equal amounts were added to single species and double species experiments. the hybridisation results of combinations of different strains were compared to those of single strains. the multiple microbial assays produced a signal pattern that matched the compounded signals of single species hybridisations. due to these results a clear differentiation of species in a multiple microbial infection is possible. some experiments were carried out based on spiked blood confirming the results of pure cultures. parallel detection showed that most probes generated weaker signal intensities when two pathogens were present in one sample. this fact would lead to a lower sensitivity when polymicrobial samples are handled which enhances the risk of false result interpretation near the detection limit. hybridisation of blood sample isolates starting from bacterial dna isolated from blood pcr and labelling protocols were optimised with respect to reducing interference of blood components. addition of glycerol and betaine reduced non-specific amplification during the pcr and labelling steps in spite of large amounts of residual human dna. by this means the yield of specific pcr product was also clearly increased resulting in equal specificities as with cultured microbes. no cross-hybridisation provoked by human dna was observed. similar results were obtained when detecting combinations of single microbes simulating multiple microbial infections as already described above. the obtained signal patterns were as specific for the added strains as those from single species microarray hybridisations. the sensitivity of the method was determined by providing a ten-fold dilution series in ml spiked blood. detection limit was found to be as low as bacteria per ml whole blood. however, as observed with pure cultures the sensitivity of gram positive bacteria is much lower, e.g. per ml blood for s. aureus. normalisation normalisation is an important aspect of all microarray experiments. usually it requires a set of probes which are expected to give a constant signal throughout all hybridisations. in the present application there are no endogenous genes or sequences to suit this requirement. therefore the only other option would be to spike known amounts of sequences similar to the 16s rrna gene into bacterial suspension before cell lysis or directly into the dna extract. however, spike controls are known to be potentially unreliable due to inaccuracies in nucleic acid quantitation and pipetting errors. also, there could be competitive effects between the spike oligonucleotide and the target 16s gene during pcr, thus introducing a bias. therefore a quantile normalisation approach was chosen, based on the assumption that each array should have a number of probes which give a positive signal and the rest of the probes a low signal. this algorithm is a between-array normalisation approach which shifts the signal density of each hybridisation towards an average density across all hybridisations. classification fig shows the clear clusters of hybridisations as well as of probes. although each probe was designed to bind to one specific pathogen, the heatmap shows that some probes are very specific to one species while others yield signals for a wider range of different organisms and a few probes do not show any specific signal at all. a classical approach would be to evaluate each probe set across all hybridisations and define a signal threshold e.g. by roc analysis to distinguish positive from negative signals. however, since some probes show cross-hybridisation between species or even genera, this would not only lead to problems with specificity, but would also mean a loss of information contained in the cross-hybridisation patterns. a machine learning approach was used to classify a hybridisation pattern by similarity to hybridisations with known organisms. the k-nearest neighbour method was used and validated in a leave-one-out cross-validation approach. at genus level, all hybridisations were classified correctly and % at species level. in cases the species p. mirabilis and p. vulgaris and in cases a. baumannii and a. radioresistens were confounded. these misclassifications are not surprising, taking into account the high sequence similarity between the respective organisms. possibly some of the misclassifications are due to low numbers of hybridisations in the test set, and could be avoided by adding more experiments to the test set. discussion the present microarray for the identification of blood isolates is so far the first microarray-based molecular diagnostic tool to identify a wide range of clinically relevant bacteria and yeast directly from blood in an appreciated period of time. another similar approach applying isolates of positive blood cultures has been published previously. the authors of this article introduce 19-mer 16s rdna signature oligonucleotides which were spotted on ta2o5- coated microarrays in order to allow evanescent-waveguide readout. hybridisation data were analysed using hierarchical clustering analysis and pattern recognition appyling a decision tree. the combination of pcr amplification with microarray hybridisation represents a powerful tool for pathogen identification. it exceeds conventional technologies in speed while performing at an extremely high specificity. analysis of 16s rrna genes has been reported before to allow a more robust, reproducible, and accurate testing than phenotypic methods. over sequences have been analyzed in the arb software package to design species- and genus-specific microarray probes and calculate the hybridisation behaviour of these probes to target dna from the respective bacterial species. predicted and experimental values showed strong correlation. short oligonucleotide probes ranging between and mer were used for this study because they allow distinct discrimination of single nucleotide differences under stringent conditions. their hybridisation properties are fundamentally different compared to long oligonucleotide probes which usually have a length of to mer thus showing higher binding capacities and thereby leading to higher detection sensitivities on a microarray. however, the threshold of differentiation of long oligonucleotide probes is at best % sequence similarity, which makes them not suitable for species identification based on the 16s rrna marker gene. other marker genes were considered as potential targets for probe design especially some genes already known for their elevated sequence variability that might allow better discrimination of members of the family enterobacteriaceae. however, an eminent advantage of the 16s marker gene is its good characterisation and the online availability of thousands of sequences. furthermore in the meantime there is an arb databank for free downloading on the homepage of the technical university munich which contains more than complete and aligned 16s rrna sequences including phylogenetic relations calculated by the neighbour joining method. additional sequences can be downloaded from any online database or manually added to the arb database. this way the accession to sequences of 16s rrna genes is possible through the ribosomal database project ii. with our approach we showed that this marker gene is well suited to discriminate even very closely related species. it was further demonstrated that analysis based on ribosomal rna can be performed in presence of a strong background of human dna. taking all the considerations into account there still remain two possible approaches for probe design. first the use of long oligonucleotide probes which allows high sensitivity. however, for equal specificity the application of several marker genes would be necessary to identify the whole panel of microbes. such an approach necessitates the realisation of a multiplex pcr that might attenuate benefits in sensitivity of long probes. further distinct species discrimination within the family enterobacteriaceae would still be difficult. on the other hand the employment of short probes targeting solely the 16s rrna gene also allows good discrimination and even species identification by pattern recognition within very closely related species. applying stringent conditions this approach even allows detection of single nucleotide differences. furthermore the use of the most characterised marker gene with the highest number of available sequences allows reliable in silico predictions based on experimentally obtained data. standard clinical identification procedures require days and up to days for microorganisms that are difficult to cultivate. in contrast to cultivation- and bacterial enrichment dependent methods microarrays enable not only a fast and accurate but also highly parallel identification of different microorganisms in one assay. the present protocol can be carried out within hours from drawing blood to the presentation of results by an analysis software, when gel electrophoresis for pcr product confirmation and pre-hybridisation are carried out in parallel with labelling reaction. most identifications were realised analysing different samples and positive as well as negative control. therefore samples had to be proceeded in parallel. the dna preparation lasted hours, the amplification reaction hours, the labelling min, the hybridisation hour, the washing minutes and the scanning also minutes. the applied mastermixes and buffers were prepared prior to the analysis in large amounts so that each solution was ready to use. thus diagnosis can be obtained within a working day when blood is collected from the patient in the morning. the current assay time of hours can be easily reduced by hours using meanwhile commercially available fast pcr devices. online fluorescence scanner or electrode chip based systems could be applied for faster assay performance. a further reduction in assay time can be achieved when dna isolation from blood is done as an automated and integrated process. such systems are currently being tested in the clinical practice. the shorter duration would allow the realisation of several detection runs per day. additionally, the handling steps would thus be reduced thereby reducing the danger of infection for personnel performing the assay. furthermore compared to cultivation-based identification procedures dna based methods have the advantage to enable even the detection of static or dead cells before genome degradation e.g. in the case of administration of antibiotics when no further growth in culture can be observed. however dna-based detection methods are not able to distinguish between alive and dead cells which might lead to misguiding therapeutic conclusions since initial antibiotic treatments are always applied prior to first blood withdrawal. in the case of multiple infections, where one species is already eradicated by antibiotics, the other species could be underestimated due to a high amount of dna from the non-viable bacteria. most studies on nucleic-acid based identification of blood-borne pathogens, including multiplex-pcr, real-time pcr and microarrays, were so far restricted to blood cultures and mostly to the identification of selected members of the enterobacteriaceae family or gram positive bacteria like staphylococcus and streptococcus. the application of microarrays for pathogen identification of clinical specimens has already been proposed earlier. amongst published tools are arrays for upper respiratory tract infections, urinary tract infections, human faeces analysis and blood stream infections. microbial detection has been achieved applying different marker genes because of known inconvenience of 16s rrna due to high sequence similarities between closely related species. the suitability of 23s rrna, the topoisomerases gyrb and pare has been proven for distinct species discrimination the small and large subunit rrna genes, virulence factors and antibiotic resistance determinants have been successfully applied as markers for the detection of bloodstream infections. however, all microarray based studies were carried out so far with clinical specimens isolated from blood culture that partially neutralises the main advantage of identification by molecular methods. on the other hand direct detection from whole blood samples implicates higher detection limits. a general limitation of microbial detection microarrays compared to blood cultures is the generation of false negative results for species with no specific probe within the panel. this study was carried out with whole blood and it was shown that no cross-hybridisation is caused by human background dna. the developed probe panel further covers the species most frequently associated with bloodstream infections and can easily be extended. the applied normalisation has the advantage that no more control is needed for correct classification of the outcomes. each result can be added to the classifier leading to even more precise calculations. the present pathogen identification microarray is to our knowledge the first microarray assay for the parallel identification of a total of blood-born bacterial species as well as clinical relevant candida species which enables pathogen identification down to cfu/ml blood without any preculturing. using this microarray for pure cultures detection limits in the range of and bacteria per assay were achieved, whereas the limit of detection for bacteria in spiked blood was found to be to bacteria per ml blood depending on the targeted microbes. since even in blood of severe sepsis patients only viable pathogenic cells per ml blood can be found this high detection limit is a clear shortcoming of this method implicating false negative results or the risk of detection of mostly dead cells thus leading to misguidance. the higher lod of spiked blood samples compared to pure cultures results from pcr inhibitory components in blood. additional dna purification can reduce the amount of these inhibitors, but high levels of residual human dna still render lower lod difficult. due to high sequence similarities of the 16s rrna gene short oligonucleotide probes were used in order to increase specificity. however, such an improvement implicates a reduction of sensitivity which also leads to strong signal variations near the limit of detection. in our study this problem could be overcome by microarray result evaluation by the developed pattern recognition which quantities and normalises signal strengths. but in routine application this fact would display a high risk of result misinterpretation near the detection limit. different approaches to increase signal intensity and to further reduce the lod of microarray analysis may be applied to this test. one possibility is the usage of a rotating microchamber for supporting the stirring of the hybridisation mix. other improvement strategies concern the choice of probes for detecting pathogens. this includes the introduction of poly-t spacers to dna probes to avoid steric hindrance during hybridisation, investigating different lengths of probes or enlarge the probe selection to several thousands in order to produce specific patterns and to cover a wide range of identifiable organisms. the presented pathogen microarray includes dna probes with an average length of 20– bp, all derived from the prokaryotic and eukaryotic small-subunit ribosomal rna gene. due to high sequence similarities in the 16s rrna gene especially among members of the enterobacteriaceae group, it was evident that not all designed dna probes would give 100% species-specific signals on the microarray. however, we could overcome this problem by taking advantage of the species-specific patterns of signals obtained after microarray hybridisation. applying a supervised k-nearest neighbour classification method all of the tested bacteria and yeasts were identified correctly at the genus level and % at the species level. high 16s rdna sequence similarity caused only misclassification in case of p. mirabilis and vulgaris and a. radioresistens and baumanii, respectively. based on this microarray different microbes of bloodstream infections are identifiable. however this panel may be expanded by further organisms as new pathogens appear in clinical routine and slight variants are observed when organisms are isolated from clinical specimens in different regions. further microorganisms could be staphylococcus lugdunensis, streptococci like s. agalactiae, salmonella spp., aeromonas spp. or candida krusei which could be easily included in the current microarray by designing species- and genus specific probes for them. a database was established serving as a classifier for the applied statistical method. this analysis method includes pattern recognition and machine learning algorithms. the chosen algorithm k-nearest-neighbour method executes an accurate identification within a fully automated platform. moreover a software package is under development which includes the flexibility of subsequent addition of single probes, individual species, groups of species or even an exchange of the whole classifier. a possible enlargement of the classifier by addition of further hybridisation results increases the specificity of identification, by reducing misinterpretation possibility due to false negative signals or cross hybridisations. such a software allows automatic processing of microarray image files and will retrieve genus and species level identification. additionally, recommendations of appropriate antibiotic treatments can be given from the statistical assessment of periodically updated information on antibiotic resistances. however, such guidance only relies on past data of statistical records. the most appropriate assistance would be gained based on antibiotic resistance determination by detection of the genetic determinants. such information can only be obtained by the realisation of multiplex pcr which would further reduce the sensitivity of the method. since seven percent of all bloodstream infections are polymicrobial, the probe pattern and the classification algorithm were also tested for randomly selected dual bacterial combinations. signal patterns from multiple microorganisms detection could be predicted from single microbe signals. in each case both pathogens present in the sample could be correctly identified. negative controls of unspiked blood gave negative pcr amplification and hybridisation results. this confirms the absence of bacteria or bacterial dna in the blood of healthy humans. the combination of microbial identification with clinical antibiotic resistance determination reveals a considerable potential. dna microarrays have already been adopted for detection of quinolone-resistant e. coli or for the genotyping of tem beta-lactamases. an antibiotic resistance microarray specifically targeted to blood-born pathogens is under development in our group following the successful establishment of a first prototype array.  in this study we have developed a rapid and sensitive method for dna based identification of clinically relevant pathogens that cause bloodstream infections. the microarray method has been shown to detect and identify pathogens down to concentrations of bacteria per ml within hours. relying on the analysis of signal patterns the assay specificity was determined to be % at genus level and more than % at species level. however, depending on clinical specimen the isolation protocol must be adapted in order to optimise microbial dna yield and to assure maximum safety to operating personnel. but the work also shows that a microarray based on the 16s rrna marker gene is a potentially powerful identification tool for routine clinical laboratory diagnostics. additionally the range of identifiable organisms can easily be extended to new pathogens and also multimicrobial infections can be considered. 
a molecular approach is presented for the rapid identification of pathogens combining pcr amplification with microarray detection. the newly developed molecular assay can be carried out within hours in a research laboratory from pathogen isolation to species identification. the observed detection limits varied from cells to cells per ml artificially spiked blood. molecular biology based techniques allow fast identification, however discrimination of very closely related species remains still difficult. from our results we conclude that dna microarrays can be a useful tool for rapid identification of closely related pathogens particularly when the protocols are adapted to the special clinical scenarios. however, early and accurate identification is a crucial requisite for fast and optimally targeted antimicrobial treatment. pathogen identification in clinical routine is based on the cultivation of microbes with subsequent morphological and physiological characterisation lasting at least hours. a prototype software providing this statistical evaluation was developed, allowing correct identification in % of the cases at the genus and in % at the species level.
 pathogen identification in clinical routine is based on the cultivation of microbes with subsequent morphological and physiological characterisation lasting at least hours. however, early and accurate identification is a crucial requisite for fast and optimally targeted antimicrobial treatment. molecular biology based techniques allow fast identification, however discrimination of very closely related species remains still difficult.  a molecular approach is presented for the rapid identification of pathogens combining pcr amplification with microarray detection. the dna chip comprises oligonucleotide capture probes for different pathogens including gram positive cocci, the most frequently encountered genera of enterobacteriaceae, non-fermenter and clinical relevant candida species. the observed detection limits varied from cells to cells per ml artificially spiked blood. thus the current low sensitivity for some species still represents a barrier for clinical application. successful discrimination of closely related species was achieved by a signal pattern recognition approach based on the k-nearest-neighbour method. a prototype software providing this statistical evaluation was developed, allowing correct identification in % of the cases at the genus and in % at the species level.  the newly developed molecular assay can be carried out within hours in a research laboratory from pathogen isolation to species identification. from our results we conclude that dna microarrays can be a useful tool for rapid identification of closely related pathogens particularly when the protocols are adapted to the special clinical scenarios. 