Detection of potentially novel bacterial components of the human skin

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bacteria such as Staphylococcus epidermidis and Propionibacterium acnes, phylotype A, the 16S. rRNA gene of .... most other sites, so that even if contamination occurs, it will be relatively .... Staphylococcus capitis ATCC27840T (L37599).
Journal of Medical Microbiology (2005), 54, 1231–1238

DOI 10.1099/jmm.0.46075-0

Detection of potentially novel bacterial components of the human skin microbiota using cultureindependent molecular profiling Itaru Dekio,1,2 Hidenori Hayashi,2 Mitsuo Sakamoto,2 Maki Kitahara,2 Takeji Nishikawa,1 Makoto Suematsu3 and Yoshimi Benno2 Correspondence

1,3

Itaru Dekio [email protected]

Received 6 March 2005 Accepted 13 August 2005

2

Department of Dermatology1 and Department of Biochemistry and Integrative Medical Biology3 , School of Medicine, Keio University, Tokyo 160-8582, Japan Microbe Division/Japan Collection of Microorganisms, RIKEN BioResource Center, Wako, Japan

Although the micro-organisms forming the cutaneous microbiota are considered to play important roles in the modification and prevention of skin diseases, a comprehensive analysis of their composition has not yet been carried out because of difficulties in determining yet-to-be-cultured micro-organisms in the samples. Swab-scrubbed forehead skin samples of five healthy volunteers were analysed by profiling 16S rRNA genes, as well as by conventional culture methods, to provide a profile of the cutaneous microbiota that included yet-to-be-cultured bacteria from normal human skin. Cluster analyses of the 16S rRNA gene sequences indicated a marked increase in diversity compared with that derived from the culture methods. Nineteen previously recognized species and 13 novel phylotypes were obtained from the analysis of 416 clones. In addition to well-known bacteria such as Staphylococcus epidermidis and Propionibacterium acnes, phylotype A, the 16S rRNA gene of which is 97 % similar to that of Methylophilus methylotrophus, was detected in three of the five samples, in one of which it was the predominant clone. Culture-independent genetic profiling of 16S rRNA genes for detecting human cutaneous microbiota has allowed us to detect potentially novel components of the cutaneous microbiota in humans.

INTRODUCTION The microbiota of human skin is unique and complex, and is made up of a mixture of different groups of micro-organisms: facultative anaerobic bacteria, such as Propionibacterium acnes; aerobic bacteria, such as Staphylococcus epidermidis; and fungi, such as Malassezia furfur (Fredricks, 2001). These micro-organisms are relatively minor members of the flora of other human organs, suggesting that the skin constitutes a front-line defence system with a unique host– parasite relationship. The identification, quantitation and characterization of micro-organisms in the skin microbiota all have a potential clinical impact, because their presence could affect the proliferation of other, pathogenic bacteria that play a crucial role in triggering various common diseases. For example, P. acnes (Leyden, 2001) and Staphylococcus aureus (Leyden et al., 1974) are involved as putative pathogens in acne and atopic dermatitis, respectively. Furthermore, some commensal bacteria of the human skin can inhibit other bacteria (Selwyn, 1975), indicating a critical role for the interactions among bacterial species. Until now, The GenBank/EMBL/DDBJ accession numbers for the 16S rRNA gene sequences of novel phylotypes (phylotypes A–M) are AB161079– AB161091.

46075 & 2005 SGM Printed in Great Britain

however, technical difficulties in the isolation of bacteria which have never been cultured in vitro have not allowed the microbial population as a whole to be described.

In this context, novel technical approaches besides culture are obviously necessary to detect yet-to-be-cultured microorganisms, to allow us to formulate a true picture of the skin microbiota. Sequence analysis of the bacterial 16S rRNA gene is one method that can circumvent some of these difficulties (Ward et al., 1990); the 16S rRNA gene is a small-subunit rRNA gene known to display species-specific evolutionary variation of the gene sequence (Nelson et al., 2000). The 16S rRNA gene is present in all known bacteria and its conserved region is suitable for amplification, and thus convenient for identification (Fredricks, 2001). ‘Universal’ primers for the gene make it possible simultaneously to amplify the genetic regions of mixtures of bacteria, including clusters of yet-tobe-cultured microbial species. Such unidentified species are known as phylotypes (Frank et al., 2003; Hayashi et al., 2002; Zhou et al., 2004), operational taxonomic units (OTUs) (Suau et al., 1999) and species-level operational taxonomic units (SLOTUs) (Pei et al., 2004). The current study was designed to determine the human skin microbiota by the 1231

I. Dekio and others

bacterial 16S rRNA profiling method. The method allowed us to detect a wide range of bacteria residing in the skin of healthy human subjects and to reveal novel phylotypes.

METHODS Subjects. The experimental protocol was approved by the Ethics

Review Committee of RIKEN. Five healthy volunteers [(a) 32 year old male, (b) 55 year old female, (c) 22 year old male, (d) 31 year old female, (e) 26 year old female] participated in the study. They did not use medicated soap in their daily life, and all except volunteer (d) did not use cosmetics daily. They were advised not to wash or touch, or apply cosmetics to, the forehead skin (the sampling area) for at least 12 h prior to the commencement of the study. Collection of samples. The open end of a sterile plastic cylinder, with

an area of 4.9 cm2 , was manually placed on the forehead skin. The area inside was scrubbed using a sterile swab (Nissui) moistened with anaerobic dilution liquid for 30 s. The dilution liquid consisted of 4.5 g KH2 PO4 , 6.0 g Na2 HPO4 , 0.5 g L-cysteine HCl.H2 O, 0.5 g Tween 80 and 1.0 g agar per litre H2 O, pre-saturated and sealed with 100 % CO2 gas. The tip of the swab was then broken with the wall of a glass tube containing 1 ml of the dilution liquid, so that the wet tip was dropped into the fluid without contamination. After sampling, the tube was immediately capped and shaken for 30 s using a vortex mixer to suspend the bacteria. A volume of 300 ìl of the suspension was used for the culture method and 200 ìl was used for the 16S rRNA gene clone library. Culture method. The collected samples were serially diluted from 10

1

to 105 using the anaerobic dilution liquid. Fifty microlitres each of the 101 , 103 and 105 dilutions were plated out on three non-selective agar plates: trypticase soybean (TS) agar (Becton Dickinson) supplemented with 5 % horse blood (Nippon Bio-Test), Eggerth–Gagnon (EG) agar (Merck), and glucose-blood-liver (BL) agar (Nissui). TS agar was cultured aerobically at 37 8C for 2–3 days. EG and BL agars were cultured anaerobically in anaerobic steel-wool jars (Hirayama Manufacturing) filled with 100 % CO2 at 37 8C for 7 days. On each agar plate, at least one area for the 101 , 103 or 105 dilutions had 4–400 colonies, and these areas were selected for analysis. At least four representative colonies, including all colony morphologies, were selected for identification. Cell morphology was examined microscopically by Gram staining, and colonies with comparable macroscopic features were counted to calculate c.f.u. per millilitre (and per 4.9 cm2 of the skin surface), and then subcultured under aerobic or anaerobic conditions on EG agar. The subcultured strains were identified using sequence analysis of the 16S rRNA gene, as described below. DNA extraction. One loop of each subcultured strain was suspended in 400 ìl of 10 % Triton X-100 (Sigma), heated to 95 8C for 5 min and then cooled to 4 8C for 2 min to extract the bacterial DNA. This lysate was subsequently used for amplification of the 16S rRNA coding region for identification of the cultured colonies by PCR sequencing.

The suspension collected for the clone library was centrifuged at 15 000 g for 2 min to form a pellet. The pellet was suspended in 500 ìl bead solution (UltraClean Soil DNA kit, Mo Bio Laboratories), then lysozyme (5 mg ml1 final concentration) and N-acetylmuramidase (1 mg ml1 final concentration) were added for degradation of the bacterial cell wall. After incubation at 37 8C for 30 min, the pellet was treated with proteinase K (2 mg ml1 final concentration) and SDS (1 %, w/v, final concentration), with constant shaking using a FastPrep instrument (Bio 101), to degrade the bacterial cell. The mixture was incubated at 70 8C for 5 min and then the UltraClean Soil DNA kit was used for extracting the DNA. This lysate was subsequently used for amplification of the 16S rRNA coding region for constructing clone libraries. 1232

Amplification of the 16S rRNA gene. Two universal primers, 27F (59

AGAGTTTGATCCTGGCTCAG 39) and 1492R (59 GGTTACCTTGTTACGACTT 39) (Lane, 1991), were used to amplify the bacterial 16S rRNA gene coding region. Amplification reactions were performed in a total volume of 50 ìl containing 2.5 ìl DNA solution extracted either from colonies isolated by culture or from primary sample suspensions, 1.25 U TaKaRa Ex Taq (TaKaRa Bio), 5 ìl Ex Taq buffer (TaKaRa Bio), 4 ìl dNTP mixture (200 ìM each final concentration) and 5 pmol of each primer. PCR amplifications were performed in a T1 Thermocycler (Biometra) with the following program: 95 8C for 3 min, followed by 30 cycles consisting of 95 8C for 30 s, 50 8C for 30 s, 72 8C for 1.5 min, and a final extension period of 72 8C for 10 min. The amplified DNA was purified using an UltraClean PCR Clean-up kit (Mo Bio Laboratories). 16S rRNA gene clone library. 16S rRNA gene clone libraries were

constructed as described by Hayashi et al. (2002). The amplified DNA was purified using an UltraClean PCR Clean-up kit. A purified amplicon was ligated into the plasmid vector pCR 2.1, then transformed into One Shot INVÆF9 competent cells using the Original TA Cloning kit (Invitrogen). For each sample, 96 transformants were picked from the agar plates. The transformants were inoculated into 23 Luria– Bertani liquid medium using 96-deep-well blocks and incubated at 37 8C, 1000 r.p.m., for 16 h. The cultured transformants were lysed and their plasmid DNA was extracted using the MultiScreen 96-well filter plate kit (Millipore). DNA sequencing and phylogenic analysis. 16S rRNA genes from

both subcultured strains and clone libraries were used as templates for sequencing. The anterior third of the 16S rRNA gene (Escherichia coli position 27–520) was used for sequence analysis. The dideoxy chain termination reaction was conducted in both directions using 27F and 520R (59 ACCGCGGCTGCTGGC 39) primers (Lane, 1991) with a double-stranded DNA template and the BigDye Terminator Cycle Sequencing kit (Applied Biosystems). The products were analysed by an ABI PRISM 3100 DNA analyser system (Applied Biosystems). The data obtained for both directions were aligned and manually corrected using AutoAssembler 2.1 software (Applied Biosystems). The nucleotide sequences were checked by the Chimera Check program (Ribosomal Database Project II, http://rdp.cme.msu.edu) (Cole et al., 2003) to eliminate chimeras which could result from the amplification of an accidental mixture of bacterial genes; however, no chimeric sequences were detected. Nucleotide sequences were analysed by a BLASTN search (European Bioinformatics Institute, in DDBJ homepage, http:// www.ddbj.nig.ac.jp) (Altschul et al., 1997) for the nearest matches. Then, sequence alignments were done using CLUSTALW (Thompson et al., 1994) software (European Bioinformatics Institute). The nucleotide substitution rate was calculated, and the phylogenetic trees were constructed by the neighbour-joining method (Saitou & Nei, 1987) using NJplot software (Poˆle Bio-Informatique Lyonnais). A bootstrap resampling analysis (Felsenstein, 1985) of 100 replicates was performed to estimate the confidence of tree topologies. The estimation of diversity coverage was calculated by Good’s method (Good, 1953), according to which the percentage of coverage was calculated with the formula (%) ¼ [1(n/N)] 3 100, where n is the number of phylotypes represented by one clone only and N is the total number of sequences. The term ‘phylotype’ is used for clusters of clone sequences which differ from known species by more than 2 % and are at least 98 % similar to members of their cluster (Suau et al., 1999). Phylotypes that have been reported in the DDBJ, EMBL and GenBank databases are called ‘known phylotypes’, and the rest of the phylotypes are called ‘novel phylotypes’.

RESULTS AND DISCUSSION In the present study, the gene-profiling method allowed us to reveal a more comprehensive view of skin microbiota, Journal of Medical Microbiology 54

Molecular profiling of skin microbiota

including yet-to-be-cultured bacteria, than that previously achieved. The results of our sequence analysis demonstrated the presence of a variety of species and phylotypes of bacteria formerly undetected in the skin microbiota. These bacteria had not been detected in the skin until now, possibly because appropriate in vitro culture conditions had not been employed.

mitis/salivarius was also isolated. From all samples, Staphylococcus species were isolated in relatively smaller numbers; all species were coagulase-negative. S. aureus was not cultured in any samples examined in this study, confirming the status of the healthy volunteers examined in the present study. All the cultured bacteria were classical known members of the skin microbiota and the total c.f.u. cm2 of the samples was of the same order as that reported previously (Evans, 1975; Marples & McGinley, 1974). The bacterial count was comparable to the results of molecular analysis, although it was not possible to describe the variation of the microbiota due to the limited number of isolates subjected to the identification procedures.

Sampling site Previous culture-based studies have revealed that skin microbiota differ widely among different sites of the body (Marples & McGinley, 1974; Marples, 1982). To investigate the host–parasite relationship under physiologically steadystate conditions, we chose the forehead skin as the sampling site for five reasons. First, the site is considered to maintain a tight host–parasite relationship, through enriched nutrient supplementation and by the antibiotic peptides of sebaceous secretions (Evans, 1975). Secondly, the site has a stable moisture level (Evans, 1975), and variations in moisture levels make surface conditions variable. Thirdly, the site is not generally covered with clothes, which differ widely from individual to individual and also with climatic conditions. Fourthly, the number of bacteria is much larger than that of most other sites, so that even if contamination occurs, it will be relatively small as a proportion of the total. Finally and most importantly, the site is suspected from a clinical microbiological point of view to participate in many pathological skin conditions, such as atopic dermatitis in adults and acne.

Species or phylotypes revealed by 16S rRNA gene analyses Among 480 transformants, 64 were not suited for sequence analysis for various reasons, such as the lack of a transformed sequence and low signals in sequencing. A total of 416 clones [61 clones from sample (a), 90 from sample (b), 91 from sample (c), 87 from sample (d) and 87 from sample (e)] were successfully obtained and sequenced from the 16S rRNA gene clone libraries. Among them, 343 clones (82 %) were those of 19 known species (Table 2). Ten species were previously reported members of the skin microbiota and nine were other known species. The majority of the clones (257 clones, 62 %) were those of P. acnes, which constituted the predominant member in culture analyses. Three species of the genus Acinetobacter, which were not detected in culture analysis, were detected by the molecular technique (16 clones, 4 %). On the other hand, 73 clones (18 %) were classified into 13 phylotypes (Table 3). The 13 phylotypes thus determined were named A to M, respectively, according to the number of clones detected for each individual phylotype.

Culture analysis P. acnes and Staphylococcus species were cultured in all samples (Table 1). The total c.f.u. cm2 varied from 3.7 3 104 to 1.2 3 106 . In four of the five samples, the majority (more than 92 % of the total c.f.u.) of the isolated bacteria were P. acnes. In sample (d), in contrast, P. acnes, Propionibacterium granulosum and S. epidermidis constituted the majority of the bacterial population, and Streptococcus

The phylogenetic tree showed a large diversity of the bacterial community, which consisted of firmicutes, actinobacteria, cyanobacteria, bacteroidetes and proteobacteria (Fig. 1). At

Table 1. Culture analysis of bacterial species isolated from forehead swabs of five healthy volunteers The five volunteers are designated (a)–(e). The values shown are c.f.u. per cm2 of skin surface. Colonies having the same plate morphology were subcultured and their 16S rRNA genes sequenced. ND, Not detected. Bacterial species

Anaerobic bacteria Propionibacterium acnes Propionibacterium granulosum Aerobic bacteria Staphylococcus epidermidis Staphylococcus warneri Streptococcus mitis/salivarius Total count

http://jmm.sgmjournals.org

Volunteer (a)

(b)

(c)

(d)

(e)

9.4 3 104

1.1 3 105

3.7 3 104

1.2 3 106

ND

ND

ND

5.3 3 104 1.6 3 104

8.1 3 101 5.7 3 103

1.1 3 103

ND

4.5 3 104

9.0 3 103

ND

6.9 3 102

ND

ND

ND

ND

ND

1.0 3 105

1.1 3 105

3.7 3 104

4.1 3 103 1.2 3 105

1.2 3 106

ND

ND

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Table 2. Bacterial species detected from 16S rRNA gene clone libraries The clones were sequenced and the databases searched for the nearest match. The sequence data accession numbers refer to the DDBJ, EMBL and GenBank databases. Bacterial species (names of representative clones)

Similarity with nearest matches (%)

Number of clones

Database accession no. of nearest matches

100–98 100 99 99–98 99–98 99 98 99 99 99

257 41 13 4 2 2 1 1 1 1

AB042288 D83363 Z93440 AJ003057 Z93434 AY188352 Z93438 AF542227 L37603 AY188347

100–99 100 100 98 99 99 99 99 99

5 4 3 2 2 1 1 1 1 343

AF320988 X95923 AJ439348 AF078766 X79290 X68416 AB042061 X87272 AF479577

Known skin microbiota Propionibacterium acnes (2E8) Staphylococcus epidermidis (4G9) Acinetobacter johnsonii (2H9, 5D5) Propionibacterium granulosum (4A3) Acinetobacter calcoaceticus (4B3, 5HZ) Streptococcus mitis/salivarius (4CZ) Acinetobacter junii (5E9) Finegoldia magna (2C9) Staphylococcus warneri (2B9) Streptococcus cristatus (4AY) Other known species Pseudomonas sp. (2A2) Stenotrophomonas maltophilia (2E5) Corynebacterium pseudogenitalium (4CY) Acidovorax temperans (3E2) Dietzia maris (1D2) Bacillus licheniformis (1H8) Bacillus subtilis (5BZ) Bradyrhizobium sp. (2FY) Neisseria subflava (5F6) Total

Table 3. Phylotypes detected from 16S rRNA gene clone libraries Here, a phylotype refers to a cluster of as-yet-unculturable bacteria which differ from known species. The clones were sequenced and searched for the nearest match in the databases. The sequence data accession numbers refer to the DDBJ, EMBL and GenBank databases. Phylotype (name of representative clone, database accession no.)

Nearest related species

Similarity with nearest matches (%)

Number of clones

Phylotype A* (3B7, AB161079) Phylotype B* (3AZ, AB161080) Phylotype C* (5C8, AB161081) Phylotype D* (2EX, AB161082) Phylotype E (2FZ, AB161083) Phylotype F* (5A2, AB161084) Phylotype G (5C2, AB161085) Phylotype H* (5H3, AB161086) Phylotype I* (5DY, AB161087) Phylotype J (3CZ, AB161088) Phylotype K (3D9, AB161089) Phylotype L* (2B9, AB161090) Phylotype M (3F1, AB161091) Total

Methylophilus methylotrophus Ideonella dechloratans Ammoniphilus oxalaticus Anabaena cylindrica Aquaspirillum autotrophicum Actinomyces nasicola Neisseria canis Peptoniphilus harei Proteus mirabilis Ralstonia eutropha Spirosoma navajo Staphylococcus epidermidis Thauera aromatica

97 94 96 91 96 87 88 97 97 97 93 97 90

53 6 2 2 2 1 1 1 1 1 1 1 1 73

Database accession no. of nearest matches L15475 X72724 Y14578 AF091150 AB074524 AJ50845 L06170 Y07839 AF008582 D87999 AY279978 D83363 X77118

*Clones of novel phylotypes whose 16S rRNA genes differ from those of previously reported phylotypes by more than 2 %. 1234

Journal of Medical Microbiology 54

Molecular profiling of skin microbiota 0.05 100

Staphylococcus caprae ATCC35538T (AB009935) 69 Staphylococcus capitis ATCC27840T (L37599) Staphylococcus aureus ATCC12260 T (L37597) Staphylococcus epidermidis ATCC14990 T (D83363) 4G9 (42 clones)

50 Staphylococcus warneri ATCC27836T (L37603) 56 2B9 (1 clone) [Phylotype L] *(AB161090) 64 Bacillus subtilis IAM12118 T (AB042061)

100

5BZ (1 clone)* Bacillus licheniformis DSM13T (X68416) 93 1H8 (1 clone)* Ammoniphilus oxalaticus RAOx-1 T (Y14578) Firmicutes 5C8 (2 clones) [Phylotype C] *(AB161081) 100 Streptococcus agalactiae JCM5671 T (AB023574) 55 Streptococcus cristatus ATCC51100T (AY188347) 4AY (1 clone) 98 100 Streptococcus pyogenes JCM5674 T (AB023575) Streptococcus salivarius ATCC7073 T (AY188352) 100 4CZ (2 clones ) 100 Finegoldia magna CCUG17636 T (AF542227) 2C9 (1 clone) Peptoniphilus harei DSM10020 T (Y07839) 100 5H3 (1 clone) [Phylotype H]* (AB161086) 100 Corynebacterium pseudogenitalium CIP106714T (AJ439348) 4CY (3 clones) * 95 Dietzia maris DSM43672 T (X79290) 100 1D2 (2 clones) * 87 100 Propionibacterium acnes ATCC6919 T (AB042288) Actinobacteria 76 2E8 (257 clones) Propionibacterium granulosum DSM20700 T (AJ003057) 72 4A3 (4 clones) 100 Actinomyces nasicola CCUG46092 T (AJ508455) 5A2 (1 clone) [Phylotype F] *(AB161084) Anabaena cylindrica NIES19 (AF091150) Cyanobacteria 2EX (2 clones) [Phylotype D] * (AB161082) Spirosoma navajo HDK660 (AY279978) 3D9 (1 clone) [Phylotype K] * (AB161089) Bacteroidetes 75

97

51

100 87

52 93

91 98 100

66

98

Bradyrhizobium japonicum DSM30131T (X87272) 2FY (1 clone) * Methylophilus methylotrophus ATCC53528 T (L15475) 3B7 (53 clones) [Phylotype A] * (AB161079) 51 Aquaspirillum autotrophicum IAM14942T (AB074524) 100 2FZ (2 clones) [Phylotype E] * (AB161083) Ralstonia eutropha DSM2839 (D87999) 100 3CZ (1 clone) [Phylotype J]* (AB161088) Thauera aromatica K172 T (X77118) 3F1 (1 clone) [Phylotype M] * (AB161091)

100 100

Neisseria gonorrhoeae NCTC8375T (X07714) Neisseria subflava NJ9702 (AF479577) 81 96 5F6 (1 clone) * Neisseria canis ATCC14687T (L06170) 5C2 (1 clone) [Phylotype G] * (AB161085) 100 Acidovorax temperans CCUG11779T (AF078766) 3E2 (2 clones) * Ideonella dechloratans strain unknown (X72724) 69 66 3AZ (6 clones) [Phylotype B]* (AB161080) 99 1 00 Stenotrophomonas maltophilia LMG958 T (X95923) 2E5 (4 clones) * 100 Proteus mirabilis ATCC29906 T (AF008582) 5DY (1 clone) [Phylotype I]* (AB161087) 100 Acinetobacter calcoaceticus ATC C23055T (Z93434) 51 5HZ (1 clone) 4B3 (1 clone) 83 Acinetobacter johnsonii ATCC17909 T (Z93440) 100 64 2H9 (12 clones) Acinetobacter junii ATCC17908 T (Z93438) 98 5E9 (1 clone) 68 55 5D5 (1 clone) Pseudomonas aeruginosa ATCC10145T (AF094713) Pseudomonas tolaasii NCPPB2192T (AF320988) 100 90 2A2 (5 clones) * 52

85

Proteobacteria

Fig. 1. Phylogenetic tree showing the relationship of the 16S rRNA gene sequences obtained from the clone libraries. The tree was constructed by the use of neighbour-joining analysis based on 16S rRNA gene sequences. When two or more identical sequences were detected, only one is shown and the total number of clones appears after the clone name. For each representative 16S rRNA gene sequence, one or more sequences of known species (type strain, if one exists) is referenced from the DDBJ, EMBL and GenBank databases. Bootstrap values of 50 % or more are considered to represent parentage. *Novel members of the skin microbiota that have not been reported as members of the skin microbiota in earlier reports. http://jmm.sgmjournals.org

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the genus level, the detected bacteria were classified into 24 genera, which indicates a much greater diversity than that of the formerly established resident bacteria, which consists of eight genera (Chiller et al., 2001). At the species level, the detected bacteria were classified into 19 species and 13 phylotypes, which included only 10 resident bacterial species formerly identified through culture methods (Tables 2 and 3) (Chiller et al., 2001; Marples & McGinley, 1974). All 19 species and 13 phylotypes were listed according to the total number of clones detected, as seen in Table 4. All samples exhibited the presence of one or more of the newly detected phylotypes, although the distribution of the individual phylotypes was heterogeneous among the samples. Among the novel members, phylotype A was detected in

three of five samples and was the predominant clone in sample (c). This phylotype may be a common but disregarded member of the skin microbiota, and its nature and role as a major member should be investigated to understand the state of the bacterial community as a whole. To clarify whether the phylotype is a universal member of the skin microbiota commonly residing in humans, specific rather than universal primers should be used because of their ability to detect the phylotype efficiently even for fewer cells. We also detected typical antibiotic-resistant opportunistic pathogens (Quinn, 1998) in skin microbiota in relatively high numbers. Three species of the genus Acinetobacter were detected in four of five samples and Stenotrophomonas maltophilia was detected in two of five samples; both genera

Table 4. Species and phylotypes detected through clone library analysis Species or phylotype

Propionibacterium acnes Phylotype A Staphylococcus epidermidis Acinetobacter johnsonii Phylotype B Pseudomonas sp. Propionibacterium granulosum Stenotrophomonas maltophilia Corynebacterium pseudogenitalium Acidovorax temperans Acinetobacter calcoaceticus Dietzia maris Streptococcus mitis/salivarius Phylotype C Phylotype D Phylotype E Acinetobacter junii Bacillus licheniformis Bacillus subtilis Bradyrhizobium sp. Finegoldia magna Neisseria subflava Staphylococcus warneri Streptococcus cristatus Phylotype F Phylotype G Phylotype H Phylotype I Phylotype J Phylotype K Phylotype L Phylotype M Total Estimate of diversity coverage (%)

1236

Volunteer

Total no. of clones

(a)

(b)

(c)

(d)

(e)

52 5

66 2 2 6 5 4

23 46 8 2

53

63

24 1

7 4

3

1

3

1

1

1

3 2 2 2 1

1 2

2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 61 97

90 97

1 91 95

87 95

87 90

257 53 41 13 6 5 4 4 3 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 416

Journal of Medical Microbiology 54

Molecular profiling of skin microbiota

cause a variety of fatal systemic infections in immunocompromised subjects, such as bacteraemia, pneumonia, endocarditis and pyelonephritis (Bergogne-Be´re´zin & Towner, 1996; Senol, 2004; Vartivarian et al., 1996). Since they are ubiquitous in the environment, e.g. in soil, tap water and crops (Seifert et al., 1997; Senol, 2004), these genera are able to survive harsh environmental conditions that occur through a wide range of physical and chemical changes. As a result, they may be able to survive the rapidly changing conditions of the surface of the skin. On the other hand, these genera have not been detected as major members of the microbiota in concise molecular analyses of the gastrointestinal tract, vagina and outer ear canal (Hayashi et al., 2002; Pei et al., 2004; Suau et al., 1999; Zhou et al., 2004; Frank et al., 2003). These findings suggest that the skin microbiota may be a reservoir of such opportunistic pathogens derived from the environment, and suggest a unique host–parasite relationship for such environmental micro-organisms. S. aureus is a clinically important transient bacterium producing various kinds of skin-damaging exotoxins and is suspected to play certain roles in skin diseases (Leyden et al., 1974). It was not detected in either our culture or our molecular analyses. Although there is a possibility that it was not detectable due to technical reasons, this is consistent with the fact that S. aureus is rarely isolated from the exposed skin of healthy humans (Ogawa et al., 1994).

Technical limitations PCR-based techniques suffer from possible biases due to the differential lysis of bacteria, the primers used in PCR, and the preferential cloning of PCR products (von Wintzingerode et al., 1997). As a result, there is a possibility that clone numbers do not reflect the proportion of bacterial cell numbers. The additional usage of a different primer set may result in the detection of other bacteria (Hayashi et al., 2004). Our molecular analysis of skin microbiota is essentially descriptive. As a result, a problem arises in that it is impossible to determine whether the bacteria detected are genuine previously disregarded skin residents, or whether they are transient, or indeed only contaminants placed on the skin before sampling. For example, Stenotrophomonas spp., Bradyrhizobium spp. and Acidovorax spp. are frequently detected in water-distribution systems in developed countries (Norton & LeChevallier, 2000; Williams et al., 2004), and Acinetobacter spp., Dietzia maris and Bacillus spp. are commonly found in soil and in lakes. To ensure that they were not laboratory contaminants, we analysed four moistened swabs as negative controls of sampling materials and four separately prepared PCR mixes (data not shown), and we detected no 16S rRNA gene in them. Ideally, contemporaneous controls should have been performed at the time of sampling. Nevertheless, these results indicate that, if present, the contamination of reagent and sampling material was relatively infrequent. http://jmm.sgmjournals.org

Comparison with other molecular analyses Our culture-independent 16S rRNA gene analyses successfully identified a variety of novel bacteria which have not been detected in similar analyses of other human organs, such as the gastrointestinal tract (Hayashi et al., 2002; Pei et al., 2004; Suau et al., 1999), the vagina (Zhou et al., 2004) and outer ear canal (Frank et al., 2003). The outer ear canal has features histologically comparable with those of facial skin. Both consist of squamous epithelium containing hair and are located on the uncovered outer surface of the human body, although the types of sweat glands are different (the outer ear canal contains apocrine sweat glands) (Kennedy, 1998). However, the molecular bacterial profile of outer ear fluid reported by Frank et al. (2003) was not consistent with our skin microbiota results. More than 87 % of the clones were of species not detected in our study: Alloiococcus otitis, Corynebacterium otitidis and Staphylococcus auricularis. This reflects the diversity in the host–parasite relationship among organs and sites on the outer surface of the human body. The skin microbiota changes with the skin condition. Hill et al. (2003) examined a biopsy specimen from a chronic leg ulcer using culture-independent analysis. The majority of the 16S rRNA gene clones obtained in the study were relatives of Proteus sp. and Morganella sp., which were undetected in our study. Such a difference could result from differences in the skin surface: skin ulcers have a raw dermal surface moistened with exudate, and the growth conditions are entirely different from the epidermal surface of normal skin as a microbiological milieu. Conclusions The involvement of known species of the microbiota in common skin diseases such as acne and atopic dermatitis has been established by conventional culture analyses (Leyden et al., 1974; Leyden, 2001; Selwyn, 1975). Although it is possible that the bacteria detected in this study included some transient bacteria of environmental origin, our results indicate that the total diversity of the skin microbiota is greater than previously considered. The micro-organismrelated aetiology of skin diseases should be fully defined in the future by analysing the overall microbial community, including the novel members. Studies are currently under way in our departments to compare the microbiota identified in both patients and normal subjects, to reveal the nature and roles of such micro-organisms. In conclusion, by means of a 16S rRNA gene clone library, we detected 22 potentially novel members of the skin microbiota, comprising 9 species and 13 phylotypes. Our results indicate that the culture-independent genetic profiling of the 16S rRNA gene is a powerful tool for investigation of the skin microbiota. Further study is required to determine the occurrence of these organisms in the human skin microbiota and their roles in health and disease. 1237

I. Dekio and others

ACKNOWLEDGEMENTS This work was supported by the 21st Century Center-of-Excellence Program for Systems Biology, and partly by the Leading Project for Biosimulation and Grant-in-Aid for Creative Scientific Research 17GS0419 from the Ministry of Education, Culture, Sports, Science and Technology of Japan.

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