rapid detection and identification of infectious pathogens in clinical samples is very challenging , but it is essential to guide the therapy and predict the outcome . traditional clinical microbial diagnostic methods like physiology and biochemical identification , serological tests , and automated detection technology , are mainly based on the conventional culturing of clinical samples . the culture turnaround time is usually 12 days for most samples , or longer for samples that require prolonged incubation , like blood cultures . more recently , once an isolate has been detected , species identification and genotyping could be performed following identification of a susceptibility test . in fact , the whole procedure could take several days or even weeks , for example , in terms of the culture time required for tuberculosis , which is 42 days in the clinical laboratory . therefore , it is not only a time - consuming process , but also is a barrier that impedes the rapid detection and identification of infectious pathogens . interestingly , these culture - based methods usually fail to identify those pathogens that can not be cultivated under standard techniques , such as viruses that can be identified through antibody - specific elisa or sequence - specific molecular methods such as polymerase chain reaction ( pcr ) assay and array hybridization technologies . with traditional culture - based diagnostic techniques being partially superseded by several methods , like matrix - assisted laser desorption ionization time - of - flight mass spectrometry , pcr , real - time pcr and molecular hybridization - based technologies , the speed and accuracy of both the diagnosis and prevention of infectious diseases have been greatly improved . for instance , an internal transcribed spacer - targeted oligonucleotide chip was successfully used to detect and identify important bacterial pathogens associated with sepsis directly from the blood sample . another study also reported the use of a multiplex real - time pcr assay to identify members of the mycobacterium tuberculosis complex . although the accuracy of pathogen identification has been improved , some newly emerging and unknown pathogens still can not be identified using these current technologies . in recent years , unbiased high - throughput sequencing ( hts ) has been applied in medical microbiology as an emerging and powerful technique due to its low cost and rapid turnaround time . some notable observations are the detection of a rapid hospital spread of antibiotic - resistant klebsiella pneumonia , distinguishing legionella pneumophila outbreak isolates from nonoutbreak isolates and identifying methicillin - resistant staphylococcus aureus outbreak isolates . recently , the use of metagenomic analysis methods , which applies hts has been proposed for infectious disease detection . although hts has an important impact on the detection of pathogens , some challenges remain due to a lack of standard operating procedures . here , we have developed an efficient , accurate and comprehensive method based on hts for the rapid detection and identification of infectious pathogens directly from clinical specimens , which can be used in the context of more challenging and troublesome diseases such as a fever of unknown origin ( fuo ) . the blood samples were collected from five patients , when they were transferred immediately to the intensive care unit ( peking union medical college hospital ) with the same symptoms as fuo . and then blood samples were processed as the following steps : centrifuged ( 4c , 10 min , 1600 g ) within 8 h , transfer plasma to another tube and delivered in dry ice type environments . two blood samples , which were referred to as updid2017 and updid2011 - 1 , were blood culture positive for pseudomonas aeruginosa and streptococcus viridians , respectively . the remaining three samples , which were referred to as updid2020 , updid2026 and updid0559 - 1 were blood culture negative . all samples were collected in sterile tubes and were centrifuged at 1600 g , and then the plasma was transferred to another tube for performing the follow - up analyses . ethical approval for the study was obtained from the institutional review board of bgi - shenzhen . all patients had signed informed consent , and samples could then be used for research only . nucleic acid ( including dna and rna ) was extracted directly from the clinical samples with qiaamp viral rna mini kit ( qiagen ) . after extraction , the reverse transcription reaction was performed with primescript rt - pcr kit to generate single strand cdna . next , the double strand cdna was obtained according to the second strand cdna synthesis kit manufacture 's instruction . finally , the reaction product was purified using the qiaquick pcr purification kit ( qiagen ) . the cdna library was constructed after end repairing , a - tailing , adapter ligation and pcr . the high - quality sequence data were generated through removing low quality reads , adapter contamination , duplication reads and discarding reads shorter than 35 bp . to eliminate the effect of the human sequence , the data were removed that was mapped to a human reference sequence hg19 using burrows subsequently , we mapped the remaining sequence to the bacterial , virus , and fungi database . for a nonredundant bacterial database , we downloaded the complete genome set of version 20140829 from ncbi ( http://www.ncbi.nlm.nih.gov/ ) . for the nonredundant viral database , we chose 100 different viruses that are associated with human health based on version r194 from genbank ( http://www.ncbi.nlm.nih.gov/genbank ) . for the nonredundant fungal database , we downloaded the fungal genomic sequences associated with human disease from ncbi . at present , our databases contain 580 genus of bacteria , and 110 species of virus that are related to human diseases , and 14 species of fungi that can cause infectious in humans . the time cost of our projected pipeline is almost 3 days ( 2 days and 10 h ) based on the current technology of library construction and sequencing [ figure 1a ] . ( a ) the framework of rapid pathogen detection , which includes dna / rna extraction , sample preparation , dna library construction , sequencing , and data analysis . the analysis took 2 days and 10 h. h stands for hour and d stands for day ; ( b ) the complete data analysis process , followed by qc , trim host sequences , and database alignment . we used the software named soapcoverage from the soap website ( http://soap.genomics.org.cn/ ) to calculate the depth and coverage of each position . for bacterium , the result with coverage more than 1% and the number of stringent reads more than 10 was adopted . for fungi , the result with coverage of more than 0.1% and the number of stringent reads of more than 50 was reserved . because of the high virus mutation rate , we chose the result with coverage of more than 10% and sequence length more than 1000 bp . the relative abundance of each microbe was made according to the following definition that modified the rpkm definition , because the pathogen content is ultimately low : rpmm = ( 10  c)/(n  l ) the rpmm represents the relative abundance of 1 million base - pairs in length , c is the number of reads that aligned to this microbe reference , n is the total number of reads , and we carried out 16s rrna identification for p. aeruginosa and s. viridians , and sequence - specific pcr identification for epstein barr virus ( ebv ) with a target fragment of 250 bp to validate the result , respectively . the primers for 16s are ( forward and reverse ) : 5-caacgcgaagaaccttacc-3 , and 5-gacgggcrgtgwgtrca-3 the ebv specific primers we used were : 5-tctggcagcttttggcctt-3 , and 5-gttggagttagagtcagat-3 subsequently , we sequenced these target products by sanger sequencing . the blood samples were collected from five patients , when they were transferred immediately to the intensive care unit ( peking union medical college hospital ) with the same symptoms as fuo . and then blood samples were processed as the following steps : centrifuged ( 4c , 10 min , 1600 g ) within 8 h , transfer plasma to another tube and delivered in dry ice type environments . two blood samples , which were referred to as updid2017 and updid2011 - 1 , were blood culture positive for pseudomonas aeruginosa and streptococcus viridians , respectively . the remaining three samples , which were referred to as updid2020 , updid2026 and updid0559 - 1 were blood culture negative . all samples were collected in sterile tubes and were centrifuged at 1600 g , and then the plasma was transferred to another tube for performing the follow - up analyses . ethical approval for the study was obtained from the institutional review board of bgi - shenzhen . all patients had signed informed consent , and samples could then be used for research only . nucleic acid ( including dna and rna ) was extracted directly from the clinical samples with qiaamp viral rna mini kit ( qiagen ) . after extraction , the reverse transcription reaction was performed with primescript rt - pcr kit to generate single strand cdna . next , the double strand cdna was obtained according to the second strand cdna synthesis kit manufacture 's instruction . finally , the reaction product was purified using the qiaquick pcr purification kit ( qiagen ) . the cdna library was constructed after end repairing , a - tailing , adapter ligation and pcr . the high - quality sequence data were generated through removing low quality reads , adapter contamination , duplication reads and discarding reads shorter than 35 bp . to eliminate the effect of the human sequence , the data were removed that was mapped to a human reference sequence hg19 using burrows subsequently , we mapped the remaining sequence to the bacterial , virus , and fungi database . for a nonredundant bacterial database , we downloaded the complete genome set of version 20140829 from ncbi ( http://www.ncbi.nlm.nih.gov/ ) . for the nonredundant viral database , we chose 100 different viruses that are associated with human health based on version r194 from genbank ( http://www.ncbi.nlm.nih.gov/genbank ) . for the nonredundant fungal database , we downloaded the fungal genomic sequences associated with human disease from ncbi . at present , our databases contain 580 genus of bacteria , and 110 species of virus that are related to human diseases , and 14 species of fungi that can cause infectious in humans . the time cost of our projected pipeline is almost 3 days ( 2 days and 10 h ) based on the current technology of library construction and sequencing [ figure 1a ] . ( a ) the framework of rapid pathogen detection , which includes dna / rna extraction , sample preparation , dna library construction , sequencing , and data analysis . the analysis took 2 days and 10 h. h stands for hour and d stands for day ; ( b ) the complete data analysis process , followed by qc , trim host sequences , and database alignment . we used the software named soapcoverage from the soap website ( http://soap.genomics.org.cn/ ) to calculate the depth and coverage of each position . for bacterium , the result with coverage more than 1% and the number of stringent reads more than 10 was adopted . for fungi , the result with coverage of more than 0.1% and the number of stringent reads of more than 50 was reserved . because of the high virus mutation rate , we chose the result with coverage of more than 10% and sequence length more than 1000 bp . the relative abundance of each microbe was made according to the following definition that modified the rpkm definition , because the pathogen content is ultimately low : rpmm = ( 10  c)/(n l ) the rpmm represents the relative abundance of 1 million base - pairs in length , c is the number of reads that aligned to this microbe reference , n is the total number of reads , and we carried out 16s rrna identification for p. aeruginosa and s. viridians , and sequence - specific pcr identification for epstein barr virus ( ebv ) with a target fragment of 250 bp to validate the result , respectively . the primers for 16s are ( forward and reverse ) : 5-caacgcgaagaaccttacc-3 , and 5-gacgggcrgtgwgtrca-3 the ebv specific primers we used were : 5-tctggcagcttttggcctt-3 , and 5-gttggagttagagtcagat-3 subsequently , we sequenced these target products by sanger sequencing . species of p. aeruginosa and s. viridians in sample updid2017 and updid2011 - 1 were found to be positively grown . for each sample , we adopted pooling sequencing with an 8 bp index for all of the samples , which improved the utilization of proton . the raw - data output was 5.1 m , 46.2 m , 4.9 m , 6.1 m and 55.7 m reads for updid2017 , updid2011 - 1 , updid2020 , updid2026 and updid0559 - 1 respectively , which fulfilled the analytical standard quantity . the result of blood culture in clinical laboratory  +  represents positive , and the remaining data were mapped to the bacterial database with the mapping rate from 0.08% to 15.22% . however , for viruses whose genome is short , the proportions were all lower than the bacterial data . only updid2026 and updid0559 - 1 samples had a higher proportion of 2.27% and 2% . using our method based on proton sequencing , we detected the presence of p. aeruginosa in sample updid2017 with the coverage of 6.7% . p. aeruginosa is a common opportunistic pathogen , and is capable of causing serious infections that can cause wound infection , otitis media , meningitis , respiratory tract infection , urinary tract infection and septicemia , with varying degrees of fever . in addition , we also found traces of other bacteria with low coverage and depth , such as azotobacter vinelandii ( a nitrogen fixing bacteria ) , escherichia coli and shigella sonnei . e. coli is an opportunistic pathogen that mainly colonizes the human gut and sometimes causes intestinal diseases and genitourinary disorders . by contrast , shigella is a pathogen that can cause bacillary dysentery . given their low coverage and depth , we thought they may be the homologous sequences that can not cause such infectious symptoms . according to our parameters and clinical symptoms , we confirmed that p. aeruginosa was the cause of fever in sample updid2017 . in sample updid2011 - 1 that was positive for s. viridians after blood culture , we did not find any trace of s. viridians or other bacteria or viral species , which suggested the possibility of a false positive in the blood culture . in fact , s. viridians is an important bacteria among normal human flora that mainly colonizes the oral microbiome , followed by the respiratory tract , gastrointestinal tract , and female genital tract . interestingly , we found ebv , namely human herpesvirus 4 , with the coverage of 86% in the sample updid0559 - 1 , which was negative when we performed blood culture . ebv is the cause of nasopharyngeal carcinoma , which is also associated with chronic fatigue syndrome , infectious mononucleosis , and lymphoproliferative diseases . in addition to ebv , we did not detect any other pathogens . due to the uncultured nature of ebv using the conventional blood culture approach for the two remaining blood culture negative samples , in addition to e. coli and shigella that were detected in other samples as fragmented and homologue sequences , we did not find any closely or relevant pathogens . to profile for positive results whatever based on culture and sequencing , detailed information on data statistics is listed in table 3 , and the coverage and depth of p. aeruginosa , s. viridians and ebv along the genomic sequence in sample updid2017 , updid2011 - 1 and updid0559 - 1 were figured out . we found that the coverage distribution of p. aeruginosa and ebv genomes were dispersed and uniform , although s. viridians contained reads in only some special regions [ figure 2 ] . the annotation result for each sample rpmm : represents the relative abundance of 1 million base pairs in length , which was similar with the definition of rpkm value . the horizontal axis represents the position of each species while the vertical axis is the corresponding bin depth ; ( b ) the coverage profile of pseudomonas aeruginosa we detected . the horizontal axis represents the position of each species while the vertical axis is the corresponding bin depth ; ( c ) the coverage profile of epstein  barr virus we detected . the horizontal axis represents the position of each species while the vertical axis is the corresponding bin depth . sanger sequencing was carried out on the original sample with 16s rrna identification for updid2017 and updid2011 - 1 , as well as sequence - specific pcr identification for updid0559 - 1 . the results showed that p. aeruginosa and ebv were present in the original samples updid2017 and updid0559 - 1 , and in rti2011 - 1 there was no trace of s. viridians , respectively [ figure 3 ] . ( a ) the result of 16s pcr validation ( updid2011 - 1 , updid2020 , updid2026 and updid2017 ) . the marker we used is trans 2k plus dna maker ; ( c and d ) is the sanger sequence of target fragments .  m  and  n  represent marker and negative control , respectively . the current diagnostic paradigm consisted of four main stages , starting with the detection of a pathogen in the sample . if a clinically relevant pathogen was detected , then this might be further tested for identification of drug susceptibility and epidemiological typing . however , for most viruses , drug susceptibility , and epidemiological typing are not performed . the traditional method of detection and identification always takes several days or even weeks , which might delay the most optimal treatment times . besides this , due to the limited resolution of the method itself , the accuracy still needs to be improved . therefore , in order to detect the pathogen directly in the clinical sample , we developed a rapid , efficient and accurate method containing experimental and bioinformatics analysis processes based on proton sequencing . the whole process including sample preparation , library construction , sequencing , data analysis and issuing reports , could take almost 3 days ( 2 days and 10 h ) . compared with the traditional clinical microbial diagnostic methods based on conventional culturing , it shortens the whole period greatly . in addition , its ability to detect pathogens that are not cultivable or unknown has improved dramatically . despite the advantage of our method shows , there are still several problems to be improved upon . in regard to the experiment process , more technologies are essential to be developed such as with low dna input based on proton sequencing . for most of the clinical samples , like blood samples , the nucleic acid content that is used for library construction after removing the majority of human cells is very low , and even at the nanogram ( ng ) scale , which will cause false negative result . this process is not only applied to blood samples , but it is also necessary to develop various methods of sample preparation for different types of samples . to optimize this process further , sample preparation must be simplified , which would reduce the turnaround time to a few hours and the need for highly skilled and trained technical staff . in the context of bioinformatics analysis , considering the present opportunistic pathogens belong to the human normal microbial flora , the threshold to determine whether a pathogen is clinically relevant should be more stringent . thus , the research aiming at the distribution , coverage and abundance of the normal microbial flora should be carried out . besides this , the database we used will be updated continuously . it would not only encompass bacterial and viral genomes , but will also incorporate fungal and protist genomes . it will also represent a catalogue of point mutations or genes that account for drug resistance , which would also be added . in the present study , we only employed our method to perform detection and identification of clinically relevant pathogens . for those sequences that are both unmapped to human sequences and microbial databases , we should determine whether they are contaminated or whether this is due to homologous sequence of other eukaryotic genomes , or novel sequences of the human genome , or even perhaps novel microbial genomic sequences that we had not discovered thus far . however , unknown pathogen identification should be considered such as mapping to the nr database according to protein sequence homology . the sensitivity of hts will cause false positive result . finally , the advancement of hts sequencing technology will reduce the time and bring down the cost of hts . with the increasing demand for rapid detection and identification of infectious pathogens in clinical samples , the method we developed would play an important role in the clinical laboratory and potentially revolutionize the capability of identifying infectious and novel pathogens .