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16S Ribosomal DNA Terminal Restriction Fragment Pattern Analysis of Bacterial Communities i

16S Ribosomal DNA Terminal Restriction Fragment Pattern Analysis of Bacterial Communities i
16S Ribosomal DNA Terminal Restriction Fragment Pattern Analysis of Bacterial Communities i

A PPLIED AND E NVIRONMENTAL M ICROBIOLOGY ,0099-2240/01/$04.00?0DOI:10.1128/AEM.67.4.1935–1939.2001

Apr.2001,p.1935–1939Vol.67,No.4

Copyright ?2001,American Society for Microbiology.All Rights Reserved.

16S Ribosomal DNA Terminal Restriction Fragment Pattern Analysis

of Bacterial Communities in Feces of Rats Fed

Lactobacillus acidophilus NCFM

CHRISTOPHER W.KAPLAN,1JOHANNA C.ASTAIRE,1MARY ELLEN SANDERS,2

BANDARU S.REDDY,3AND CHRISTOPHER L.KITTS 1*

Environmental Biotechnology Institute 1and Dairy Products Technology Center,2California Polytechnic State University,

San Luis Obispo,California 93407,and American Health Foundation,Valhalla,New York 105953

Received 16August 2000/Accepted 6January 2001

16S ribosomal DNA terminal restriction fragment patterns from rat fecal samples were analyzed to track the dynamics of Lactobacillus acidophilus NCFM and discern bacterial populations that changed during feeding with https://www.wendangku.net/doc/408607739.html,ctobacillus johnsonii and Ruminococcus ?avefaciens were tentatively identi?ed as such bacterial populations.The presence of L.johnsonii was con?rmed by isolation from feces.

Many efforts to study microbial communities in the gastro-intestinal tract have focused on the large bowel and conse-quently on fecal samples (9,10,17,22,23,24).Several methods for following the complex communities in the large bowel have been employed.However,because of the abundance and di-versity of bacteria in feces,this has proved a dif?cult task.One method well suited for studying complex bacterial communities is the analysis of terminal restriction fragment (TRF)patterns (also known as terminal restriction fragment length polymor-phism analysis),which can provide a rapid and reproducible means observing bacterial population dynamics.The goal of this report was to explore a method for analyzing TRF patterns that can be used to track the dynamics of speci?c populations of bacteria in complex communities such as those in feces.TRF patterns are created by endonuclease digestion of DNA from a PCR using one ?uorescently labeled primer.Only the terminal restriction fragments are visualized after electro-phoretic separation on a DNA sequencing machine.When the target of PCR is 16S ribosomal DNA (rDNA),then the TRF pattern re?ects the taxonomic diversity of the bacteria in the sample (7,11).This method was used to compare bacterial communities from different environments with clear success (7,10,11,12,13,15,20).Comparing TRF patterns taken at different times can also monitor temporal changes in bacterial community structure.

While TRF pattern analysis allows rapid monitoring of en-vironments over time and space,it does have drawbacks.The ability of TRF patterns to accurately describe complex bacte-rial communities is complicated by variations in the conserved 16S rDNA sequences commonly used as PCR priming sites.Primer selection can dramatically alter the picture that is pre-sented in a TRF pattern,because only a fraction of the bacte-rial 16S rDNA sequences in a sample will be ampli?ed.In this study we used primers shown to hybridize well with 90%(46f)and 99%(536r)of the ?1,500bacterial 16S rDNA sequences

tested in a study by Brunk et al.(5).In addition to the coverage provided by PCR primers,there is the concern of TRF length overlap.Phylogenetically distant bacteria might produce TRFs of different lengths when digested with one endonuclease but result in TRFs of the same length when digested with a differ-ent enzyme.Thus,a more complete picture of the bacterial community is provided by an analysis of TRF patterns derived from multiple-enzyme digests.The use of several enzyme-de-rived TRF patterns can also provide data that allow the iden-ti?cation of bacteria involved in population shifts during a study (2,3,16).

The samples for this study came from an experiment re-ported by Rao et al.on colon carcinogenesis in rats fed L.acidophilus NCFM (18).Rao et al.showed that dietary NCFM suppressed the formation of precancerous lesions in the colons of rats injected with azoxymethane (18).The rats were injected with azoxymethane at 7weeks and sacri?ced after reaching 16weeks of age.We received combined fecal samples collected at 7and 16weeks of age from three groups of rats (one cage per group).Each sample was stored at ?70°C and consisted of pellets collected over a 24-h period from each cage (three rats per cage).Each group was fed the same diet except that the amount of NCFM was varied.Table 1shows the sample names,diets,and ages of the rats these samples came from.This study used TRF pattern analysis to follow NCFM content in the feces and monitor changes in the fecal bacterial communities.Creating TRF patterns for analysis.Each sample was ho-mogenized by pulverization under liquid nitrogen.DNA was extracted from 100mg of sample using a MoBio (Solano Beach,Calif.)Ultraclean Soil DNA Kit by the manufacturer’s protocol.Ampli?cation of the template DNA was performed by using a 5?-FAM-labeled primer,46f (5?-FAM-GCYTAA CACATGCAAGTCGA;Applied Biosystems Inc.,Fremont,Calif.),and unlabeled primer 536r (5?-GTATTACCGCGGCT GCTGG).Reactions were carried out in triplicate with the following reagents in 50-?l reaction mixtures:template DNA,10ng;1?buffer (Promega);deoxynucleoside triphosphates,0.6mM;bovine serum albumin,0.8?g/liter;MgCl 2,3.5mM;46f,0.2?M;536r,0.2?M;and Taq DNA polymerase (Pro-mega),2U.Reaction temperatures and cycling for fecal sam-*Corresponding author.Mailing address:Environmental Biotech-nology Institute,California Polytechnic State University,San Luis Obispo,CA 93407.Phone:(805)756-2949.Fax:(805)756-1419.E-mail:ckitts@https://www.wendangku.net/doc/408607739.html,.

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ples were as follows:94°C for2min;35cycles of94°C for2 min,48.5°C for1min,and72°C for1min;and one cycle of 72°C for10min.Primers were removed and amplicons were concentrated using the MoBio PCR Clean-Up kit according to the manufacturer’s protocol.Fluorescently labeled DNA(200 ng)was cut with one restriction endonuclease enzyme—Msp I, Dpn II,or Hae III(2.0to4.0U;New England Biolabs,Beverly, Mass.)—in the manufacturer’s recommended reaction buffers. Reaction mixtures were incubated for5h at37°C and then immersed in a65°C water bath for20min.After ethanol

precipitation the DNA was dissolved in18?l of formamide (Bio-Rad,Benecia,Calif.),with1?l each of Genescan Rox500 (Applied Biosystems)and Rox550-700(BioVentures,Mur-freesboro,Tenn.)size standards.The DNA was denatured at 95°C for5min and snap-cooled on ice.Samples were run on an ABI Prism310Genetic Analyzer.Genescan3.1software with a50-U detection threshold,Local Southern size matching, and heavy smoothing were used to quantify the electrophero-gram output.

Sample data consisted of the size(base pairs)and peak area for each TRF peak in a pattern.Because the amount of DNA loaded on the capillary cannot be accurately controlled,the sum of all TRF peak areas in a pattern(total peak area)varied between TRF patterns.To compensate for this variation,it was necessary to normalize peak detection thresholds and peak areas.The peak detection threshold was normalized by creat-ing arti?cial detection thresholds for each sample.The new threshold value was created by multiplying a pattern’s relative DNA ratio(the ratio of total peak area in the pattern to the total peak area in the sample with the smallest total peak area) by580area units(the area of a peak at the50-U detection threshold).TRF peaks with areas less than the new threshold value for a sample were removed from the data set(Table2). Peak areas were then normalized by converting the value of each remaining peak area to parts per million of the new total area.

Monitoring Lactobacillus acidophilus NCFM in feces.All the TRF patterns for rats fed NCFM included a large TRF peak2 to3bp smaller than that predicted for NCFM by rDNA se-quence analysis(Table3).A pure culture of NCFM produced the same size TRF peak as the one seen in the fecal patterns. This difference between predicted and observed TRF length has been described previously,though not fully explained(4,7, 11,13).

Visual inspection of the TRF patterns shows a large NCFM-associated peak in feces from rats fed NCFM,in contrast to a very small peak in those not fed NCFM(Fig.1).Fortunately, there appeared to be very few bacteria with the same TRF peaks as NCFM in the feces of rats not fed NCFM(Table4). Regardless of the enzyme used to create a TRF pattern,TRF peak areas increased with dietary NCFM content.In fact,the relative amount of peak area attributable to NCFM doubled in rats fed twice as much NCFM(Table4).This does not neces-sarily imply that the feces harbored twice as many live cells of NCFM because PCR was performed on DNA extracted di-rectly from the feces and could have been isolated from non-viable cells.

The ability of TRF patterns to detect the relative amount of NCFM DNA in the feces suggests that TRF patterns may be used for the relative quantitation of some bacteria in complex communities.In fact,Clement and Kitts reported a one-to-one correspondence between the proportion of NCFM cells added to a fecal sample and the percentage of the total TRF peak area present as L.acidophilus TRF peaks(6).This correspon-dence may be in?uenced by both PCR primer homology and 16S rDNA copy number in L.acidophilus.Previous papers have postulated that an average bacterial community has3.8 16S rDNA copies per genome(8)and L.acidophilus has four copies(19).

Monitoring changes in fecal communities.While the num-ber of samples collected in the study of Rao et al.was too small to produce statistically signi?cant data(18),we were interested in testing methods for analyzing TRF patterns to detect spe-ci?c organisms that contribute to differences in bacterial com-munities.A combination of principal component analysis (PCA)and database matching was investigated. Covariance PCA(21)was performed on normalized data sets consisting of TRF peak areas combined from all three

TABLE1.Rat fecal samples with respective diets as received from the American Health Foundation for use in this study

Fecal sample Age(wk)Probiotics in the diet

YR0%7Control

YR2%72%L.acidophilus(4.2?109CFU/g) YR4%74%L.acidophilus(8.4?109CFU/g) OR0%16Control

OR2%162%L.acidophilus(4.2?109CFU/g) OR4%164%L.acidophilus(8.4?109CFU/g)

TABLE2.Example of truncation procedure used to determine smallest observable peak for each sample in a data set

Sample Total area

(area units)Ratio of total

peak areas

Threshold value

(area units)

Smallest200,0001:1580a Big400,0002:11,160 Bigger2,000,00010:15,800 a Minimum detectable peak area with Genescan software.

TABLE3.TRF peak matches to organisms from

the RDP database

TRF peak set a and

organism

TRF matching length for:

Msp I Dpn II Hae III TRF peaks in the L.acidophilus set141156207 Lactobacillus acidophilus NCFM144158209 Lactobacillus crispatus143157208 Lactobacillus amylovorus141155206 TRF peaks in the L.johnsonii set149287293 Lactobacillus acidophilus ssp.johnsonii151288294 Lactobacillus gasseri151288294 Lactobacillus johnsonii151288294 TRF peaks in the R.?avefaciens set243233264 Ruminococcus?avefaciens(5strains)244234264 Unidenti?ed rumen bacterium(3clones)244234264 Ruminococcus?avefaciens(1strain)246236266 Unidenti?ed rumen bacterium(1clone)246236266 a TRF peak sets(data in boldface type)were seen in TRF patterns(Fig.3), while TRF lengths ascribed to organisms were predicted from16S rDNA se-quences in the RDP database.

1936KAPLAN ET AL.A PPL.E NVIRON.M ICROBIOL.

enzyme-derived TRF patterns.Samples from rats with NCFM in their diet (samples YR 2%,YR 4%,OR 2%,and OR 4%[Table 1])were analyzed after removing peaks speci?c to NCFM to prevent PCA from separating the samples based solely on the dominant NCFM peaks.PCA produces a collec-tion of loadings for each principal component that describes the relative contribution of each variable to the principal com-ponent score for a sample (21).This allows an investigator to focus on those variables (TRF peaks in this case)that contrib-ute to differences in principal component scores between sam-ples.The TRF peaks with large loadings can then be matched to database-predicted TRF lengths for presumptive identi?ca-tion of signi?cant bacterial populations.The ?rst principal component (PC1)appeared to separate samples based on the age of rats (sample group YR versus OR [Fig.2]).The second principal component (PC2)appeared to separate samples by NCFM content (0%versus 2and 4%[Fig.2]).This suggested that some bacteria differed in levels of abundance in the rat feces depending on age and/or diet.

For each sample,TRF pattern data from the three enzyme digests were used to look for matches to database-predicted TRF lengths.16S rDNA sequences from the Ribosomal Database Project (RDP)7.1(14)were used to create a new database containing the calculated TRF peak sizes for 6,358organisms after PCR with primers 46f and 536r.To identify bacteria in a fecal sample,each organism from the database was compared to the TRF peaks from three different enzyme digests using a Microsoft Excel macro.Differences are com-monly reported between observed TRF lengths and those pre-dicted by sequence analysis (5,6,11,13).To compensate for this discrepancy,an observed TRF (from a sample)was al-lowed to be within ?1to ?4of the predicted TRF length (in the database).

TRF peaks with large,congruent loadings for PC1were then used to search through database matches to identify presump-tive bacterial species whose abundance differed with the age of the rats.Two sets of TRF peaks clearly ?t these criteria and were thus chosen for closer investigation (Fig.2).The TRF peak sets were named for bacteria in the database that matched the set (Table 3).We could now monitor two TRF peak sets that showed different dynamics during the study of Rao et al (18).

Lactobacillus johnsonii TRF peak set.Peak areas from the L.johnsonii set were more abundant (1.8to 6.7%)in young rats than in old rats (0.3to 2.2%)as visualized in the PCA graph (Fig.2).Peak areas decreased as the rats aged,

regard-

FIG.1.Close-up of Hae III-derived TRF patterns from young rats in the study.The TRF patterns from feces of rats not fed NCFM (A)and from feces from rats fed 2%NCFM (B)are shown.Peaks of interest in this study are labeled for ease of discussion (Lba,L.acidophilus NCFM).

V OL .67,2001TRF ANALYSIS OF FECAL FLORA IN RATS FED L.ACIDOPHILUS 1937

less of dietary NCFM (Table 4).A similar decrease in NCFM peak areas was seen as the rats aged.Since both species of lactobacillus decreased in relative abundance,perhaps some-thing changed in the older rat’s cecal environment that made it less hospitable to lactobacillus species in general.

To con?rm the presence of L.johnsonii in the feces,three different bacteria were isolated at random from two fecal sam-ples (YR 0%and YR 4%).Rat fecal samples were diluted and plated on MRS agar (Difco,Sparks,Md.).Colonies were picked and streaked twice for purity.DNA from each isolate was then processed for TRF analysis as described above.All three bacteria produced TRF peaks identical to the L.johnso-nii TRF set.Extracted DNA samples were ampli?ed for se-quencing by PCR as described above except that the forward primer was replaced with unlabeled 8df (5?-AGAGTTTGTT

CMTGGCTCAG).Sequencing reaction mixtures (10?l)con-tained DNA,4ng;primer,1?M;ABI Big Dye (Perkin-Elmer),4?l;and PCR water,0.4?l.Samples were run on an ABI 377DNA sequencer,and the resulting sequences were analyzed in Autoassembler (Perkin-Elmer).A BLAST search of the sequences gave L.johnsonii as a 99%match.This indicates not only that L.johnsonii was actually present in the feces but also that it was numerically abundant enough to be easily isolated after the freezing and processing steps the feces were taken through.

Ruminococcus ?avefaciens TRF peak set.In seven-week-old rats the R.?avefaciens set represented an average of 5%of the total peak area in control rats,while those fed NCFM showed an average of 1.7%.By age 16weeks,the average peak area of the R.?avefaciens set had increased to 6%in the NCFM-fed rats and 7%in the controls (Table 4).In contrast with L.johnsonii ,this suggests that R.?avefaciens was adversely effected by NCFM at an early stage but eventually reached levels similar to those of the controls in spite of the continuing presence of NCFM.Perhaps NCFM altered the cecal environ-ment in such a way that R.?avefaciens growth was inhibited in young rats.The increase in R.?avefaciens TRF peak areas to levels similar to those seen in control rats by 16weeks of age suggests that this effect was only temporary.Perhaps the in-hibitory effect against R.?avefaciens in young rats was dimin-ished as the levels of NCFM dropped in the older rats.Rao et al.found that feeding NCFM correlated with a signi?cant decrease in fecal ?-glucuronidase activity (18).It is not unrea-sonable,therefore,to expect to ?nd altered TRF peak areas corresponding to bacteria known to produce ?-glucuronidase enzymes.Intriguingly,Ruminococcus species have been re-cently reported to express ?-glucuronidase (1).

Conclusions.Although no obvious mechanism behind the bene?cial health effects seen in the Rao et al.study could be ascertained here,TRF patterns proved to be a useful tool for monitoring the effects of probiotic dietary supplements on bacterial community structure.TRF pattern analysis clearly has the ability to detect changes in bacterial communities due to the introduction of probiotic supplements.Unfortunately,the statistical signi?cance of the observed differences in TRF patterns could not be accurately assessed in this case because the feces of three rats per treatment were combined during sampling.However,TRF patterns were able to identify organ-isms involved in the dynamics of bacterial community struc-ture,a con?rmation of suggestions by researchers using this tool (2,3,10,16).The isolation of fecal L.johnsonii strains producing the exact TRF peaks seen in fecal TRF

patterns

FIG.2.PCA of three combined TRF patterns for each fecal sam-ple.Data for each sample consist of TRF peak areas from all patterns made after digestion with each of the three enzymes.Arrows represent principal component loadings for the TRF peak sets listed in Table 3:arrows with solid lines,L.johnsonii set;arrows with dashed lines,R.?avifaciens set.The TRF lengths (base pairs)and enzymes (M,Msp I;D,Dpn II;H,Hae III)are indicated.Percent variation covered by each principal component is indicated in parentheses in the axis titles below and to the left,along with principal component scores.The right and top axes show values for principal component loadings.

TABLE 4.Peak areas from each fecal sample for each TRF peak set

Fecal sample

Mean (SD)peak area (%of total area)when indicated enzyme was used

L.acidophilus TRF peak set

L.johnsonii TRF peak set R.?avefaciens TRF peak set Msp 141

Dpn 156

Hae 207

Msp 149

Dpn 287

Hae 293

Msp 243

Dpn 233

Hae 264

YR 0%0.1(0.0)0.0(0.0)0.4(0.4) 1.8(1.0) 2.1(0.4) 3.0(0.4) 5.1(1.5) 4.3(0.7) 4.4(1.4)YR 2%9.5(1.2)9.7(4.1) 6.1(2.6) 6.2(1.9) 6.7(0.1) 6.4(0.3) 1.8(0.9) 2.9(0.9) 2.9(1.0)YR 4%13.5(3.3)15.3(1)15.2(10.8) 1.8(0.8) 3.2(0.6) 2.5(0.3)0.5(0.2) 1.2(0.1)0.8(0.4)OR 0%0.0(0.0)0.0(0.0)0.2(0.2)0.9(0.1) 1.7(0.4) 2.0(0.7) 4.3(0.4)7.2(0.4)9.6(0.4)OR 2% 4.6(1.3)8.5(3.9) 6.1(1.3) 1.1(0.2) 2.2(0.4) 1.9(0.5) 3.4(0.4) 6.1(0.7) 6.5(1.7)OR 4%8.7(4.1)11.6(1)9.6(2.7)0.3(.01) 1.9(1.8)0.5(0.2) 3.6(2.1)7.1(1.0)7.0(0.5)

1938KAPLAN ET AL.

A PPL .E NVIRON .M ICROBIOL .

after a database search predicted the presence of this bacte-rium con?rmed the accuracy of this method.The ability to associate TRF peaks with organisms allowed a deeper under-standing of bacterial community dynamics with some unfore-seen results.The addition of L.acidophilus NCFM to the young rat’s diet appeared to inhibit the growth of an R.?avi-faciens strain and decrease?-glucuronidase activity(18).Why this happened,whether it is a reproducible effect,and what the signi?cance of this interaction might be are now topics for investigation in a new study designed speci?cally to explore these?ndings.

Thanks are due to the Environmental Biotechnology Institute at Cal Poly San Luis Obispo for funding this study and to the Unocal Cor-poration for their support of TRF studies that has provided the foun-dation for this study at the EBI.

We also thank the staff at EBI that helped with the research:Raul Cano,Brian Clement,Tobe Cox,and Alice Hamrick.

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V OL.67,2001TRF ANALYSIS OF FECAL FLORA IN RATS FED L.ACIDOPHILUS1939

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建筑设备基础知识与识图

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一、判断:(每题2分,共20分) 1、为了检验各卫生器具与连接件接口处的严密性,卫生器具安装完毕必须进行通水试验。(×) 2、高压蒸汽采暖系统可以采用重力回水或者机械回水方式。(×) P262 3、大型民用建筑设施的供电,一般电源进线为6~10kv,经过高压配电所,再用几路高压配电线,将电能分别送到各建筑物变电所,降为380/220V低压,供给用电设备。(×) 4、风机出口要有不小于管道直径的5倍的直管段,以减小涡流和阻力。( ) P2785、PE线和PEN线上一般不允许设开关或者熔断器。(√ ) P265 6、低压断路器又称低压自动空气开关。它既能带负荷通断正常的工作电路又能在短路、过负荷及电路失压时自动跳闸,因此被广泛用于低压配电系统中。(√ ) 7、管道布置应该遵循水管让风管,有压管道让无压管道原则。() 8、全自动楼梯过道照明开关可根据声音传感装置随时提供照明。(×)

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