土壤微生物多 样 性多 样 性是什 么?
Size
shape
metabolic activity
nutrient requirement
oxygen requirement
habitats [temperature,pH,ionic concentrations]
形 态 多 样 性
Morphological characteristics in general are related to t
he way we visually perceive the features of an organis
m; its size and shape
From our perspectives,plants and animals have extensi
ve morphological diversity
For microbes,morphological diversity is limited
– Size and shape of cells
– Size and shape of colonies formed by bacteria
Morphological diversity is very limited for microbes
– There are probably millions of species of prokaryotes,and just
3 basic shapes of cells
– Colony morphology descriptions are also limited
Estimate thousands of species; how many colony types were obse
rved in lab?
生理多 样 性
What is the range of environmental parameters
under which organisms can survive?
Who lives where and under what conditions?
Consider physical/chemical parameters of the e
nvironment
– Temperature,light,O2,pH,pressure,etc.
Microbes have extensive physiological diversity
– They live in many environments uninhabitable by euk
aryotes
e.g,all of the above,plus deep subsurface rocks,pH 0 wat
ers,hot springs,antarctic ice fields,121°C water (250°F!)
微生物代 谢 多 样 性
Microbes have extensive metabolic diversity
– Photoautotrophy
Oxygenic photosynthesis AND anoxygenic photosynthesis
– Photoheterotrophy (not photosynthesis!)
Use light energy and organic compounds to make biomole
cules
Only Prokaryotes can do this!
– Chemoautotrophy
Use inorganic compounds for energy to fix CO2
– Several different compounds can be used
Only Prokaryotes can do this!
– Chemoheterotrophy
Use organic compounds for both carbon and energy
Often the same compound is used for both
Huge array of organic molecules are food for microbes,in
cluding many that are toxic or deadly to other organisms
遗传 多 样 性
True and heritable differences in genes (DNA
sequences) between organisms
Consider:
1,Morphological diversity
2,Physiological diversity
3,Metabolic diversity
4,Genetic diversity
1,2,3 can all be manifested at the genetic le
vel,and many times are
Genotypic differences (true genetic differences)
However,1,2,3 can also result from differen
t patterns of gene expression
Phenotypic differences (observable traits)
微生物多 样 性 评 价
从 多 个 方面
1,Morphological diversity
2,Physiological diversity
3,Metabolic diversity
4,Genetic diversity
需要多 种 新的方法形 态学评 价
Cell morphology
– Size and shape of cells
– Inclusions (e.g,endospores)
– Numbers and distribution of appendages
– Measured by light microscopy,e- microscopy
Special or differential stains (e.g,Gram stain) are often use
d
Colony morphology
– As done in lab exercise
Can characterize based on size,shape,color,outline,eleva
tion,refractility,other features
生理 学评 价
Examine biological parameters under a v
ariety of conditions
– Activity
– Growth (doubling time)
– Survival (persistence)
– Community diversity
Commonly assessed parameters:
– Temperature,pH,oxygen requirements,hal
otolerance,antibiotic/metal resistance
代 谢 和生化 评 价
Determine ranges of carbon sources used
Determine redox couples (electron donors
and acceptors) used for metabolism
Measure products formed
– CO2 evolution from aerobes
– Gases produced by fermenters
– Products from partial metabolism
– Toxic waste products
遗传 多 样 性 评 价
Generally use molecular techniques
– Phylogenetic analysis
– PCR/DGGE
Polymerase chain reaction/denaturing gradient gel electroph
oresis
– REP fingerprints
Molecular tools are providing more rapid and rel
iable means for measuring diversity and how it r
esponds to changing conditions
系 统发 生分析
The limited fossil record and structural simplicit
y of prokaryotes created great difficulties in de
veloping a classification of prokaryotes
A breakthrough came when Carl Woese and his
colleagues began to cluster prokaryotes into ta
xonomic groups based on comparisons of nucl
eic acid sequences
– Especially useful was the small-subunit ribosomal R
NA (SSU-rRNA) because all organisms have riboso
mes
Comparing sequences of these genes allows development
of a phylogenetic tree
Fig,27.13
Use conserved sequences to capture variable signat
ure sequences to establish a phylogeny of prokaryot
es and Eukaryotes; the,Tree of Life”
All three domains seem to have genomes that are chi
meric mixes of DNA transferred across the boundaries
of the domains.
This has lead some researchers to suggest replacing t
he classical tree with a web-like phylogeny
遗传 多 样 性分析 ——PCR-DGGE
采集土样 （ 3个重复,0.5g土 ）
DNA提取 （ DNA SPI试剂盒 ）
纯化 （ 用 FAST DNA PREP
SYSTEM清除蛋白质和其他杂质
） 获得 DNA模板顺向引物 27F(5’-
[6FAM]A GA GTTTGATCCTGGCTCA G-
3’) 和 反 向 引 物 338R(5’-
GCTGCCTCCCGTA GGA GT-3’)合成
0.06% 牛血 清白蛋 白,1.5mM MgCl2,2单位 Taq
DNA聚合酶,1× PCR缓冲液
ATP,TTP,
GTP,CTP
各 0.2 mM
10 ng 0.2 uM
94℃ 初始变性 3分钟
94℃ 变性 45秒
55℃ 退火 45秒
72℃ 延长 2分钟
25次
72℃ 保持 7分钟取 1ngPCR产物宽区聚丙烯酰氨凝胶电泳
PCR-DGGE基本步骤聚丙烯酰氨变性梯度凝胶电泳 条带分析建立系统树
DGGE
Denaturing Gradient Gel Electrophoresis
Separated DNA of same size based on se
quence differences.
Different sequences,behave differently at
different amounts of denaturing chemical
(or heat; see TGGE)
At some point DNA strand completely sep
arate.
Complete separation is hindered by GC-cl
amp added to one of the PCR primers.
Gradient Perpendicular to Electrop
horesis to Optimize Run
DGGE
Denaturing Gradient Gel
Electrophoresis (DGGE)
Urea/Formamide Gradient
Separates double stranded
DNA based on sequence
Muyzer et al.,1993
DGGE
Banding patterns are representative
of microbial community structure
Bands were excised
Eluted DNA was reamplified
using PCR
Band purity was verified with
DGGE
Sequencing and phylogenetic
analysis
Microbial Community Structure
of Hopane-Degrading Cultures
LC JI WS ET TC
Analysis of Bands Excised from DGGE
Profiles of Enrichments A and B
A B
ND
Alcaligenes sp,(.992)
P,azotoformans (.980)
Burkholderia cepacia (.997)
P,aeruginosa (.833)
Frateuria aurantia (.839)
ND
P,echinoides (.771)
Rhizobium/Brucella/
Ochrobactrum (.951)
Rhizobium sp,(.948)
ND
Commomonas sp,(.955)
ND
ND
P,rhodasiae (.927)
Alcaligenes sp,(.920)
ND
Burkholderia cepacia (.639)
P,alcaligenes (.696)
Strentophomonas sp,(.973)
P,echinoides (.808)
Sphingomonas sp,(.797)
Duganella zoogloides (.960)
Acetobacter sp,(.752)
Closest RDP Sequence (Sab) Closest RDP Sequence (Sab)
Phylogenetic Tree
Beta Subdivision
Burkholderia Group
Gamma Subdivision
Xanthomonas Group
Gamma Subdivision
Pseudomonas Group
Beta Subdivision
Acidovorax Group
Alpha Subdivision
Rhizobium Group
Alpha Subdivision
Sphingomonas Group
代 谢 多 样 性分析代 谢 多 样 性分析（功能多 样 性分析）
——碳 源利用方式分析（ BIOLOG分析）
BIOLOG自动微生物鉴定系统利用微生物对不同碳源利用率的差异，在大量研究基础上，设计筛选出 95种不同的碳源,检测细菌细胞利用不同碳源进行新陈代谢过程中产生的酶与四唑类物质（如 TTC,TV）
发生颜色反应和浊度差异为基础，运用显型排列技术检测出每种微生物的特征指纹图谱。在大量试验和数学模型基础上，
建立起指纹图谱与微生物种类相对应的数据库。 接种菌悬液到 96孔板后培养一定时间，通过仪器测定吸光度和浊度，与标准菌株数据库进行比对，得出最终鉴定结果。
原理方 法
称取 10g新鲜土置于 100 ml无菌水中，振荡 2
0分钟。用无菌水稀释到 10－ 3后，用 8通道加样器向 Biolog GN 微孔板 (Biolog,Inc.,Hay
ward,USA)各孔中分别添加 150 ul稀释后的悬液。每个土壤样品做 3个重复。 30℃ 恒温培养,48h后在 Emax自动读盘机上利用 Microlo
g Rel4.2软件读取 750 nm 和 590 nm波长下的光吸收，统计分析利用 SPSS10.0软件完成。
接种
将调整好浊度的菌悬液倾入 V型加样槽
采用 8通道移液器吸取菌悬液，添加 微孔鉴定板（ Microplate）
获取结果
将微孔板放入读数仪中读数，系统自动给出鉴定结果
0.000
0.200
0.400
0.600
0.800
1.000
1.200
0 50 100 150 200
培养时间（小时）
平均吸光值
（A
W
C
D
）
FACE-上
FACE-下
CK-上
CK-下多 样 性指 数 分析利用方式
use pattern AWCD
Shannon
index
Shannon
evenness Simpson index McIntosh index McIntosh Evenness
漏水型土露地蔬菜 PlOF 0.949(0.036)* 4.444(0.018) 0.982(0.002) 82.017(1.321) 9.961(0.298) 0.993(0.000)
漏水型土大棚蔬菜
PlPG
0.271
(0.019)
3.360
(0.027)
0.787
(0.028)
23.536
(0.216)
5.304
(0.354)
0.900
(0.011)
漏水型土稻麦轮作
PlRW
0.936
(0.057)
4.475
(0.017)
0.984
(0.001)
84.714
(1.510)
9.664
(0.504)
0.994
(0.000)
囊水型土露地蔬菜 WlOF 0.944(0.094) 4.415(0.031) 0.977(0.001) 79.075(2.741) 10.086(0.829) 0.991(0.001)
囊水型土大棚蔬菜 WlPG 0.164(0.012) 3.781(0.047) 0.835(0.006) 29.189(1.148) 2.883(0.204) 0.909(0.004)
爽水型土露地蔬菜
PmOF
0.991
(0.010)
4.436
(0.012)
0.975
(0.002)
79.824
(0.974)
10.546
(0.064)
0.990
(0.001)
爽水型土大棚蔬菜 PmPG 0.115(0.044) 2.768(0.771) 0.828(0.048) 14.000(10.733) 0.032(0.002) 0.849(0.053)
爽水型土稻麦轮作 PmRW 0.863(0.092) 4.422(0.027) 0.981(0.001) 80.194(1.832) 9.148(0.864) 0.993(0.000)
单一碳源利用方式典型变量因子载荷图
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
-0.
4
-0.
2
0 0.2 0.4 0.6 0.8 1 1.2
PlOF PlPG
PlRW WlOF
WlPG PmOF
PmPG PmRW
CV 1
CV2
土壤微生物群落 结构 多 样 性分析
——PLFA/FAME Analyses for
Microbial Community Assessm
ent
什 么 是磷脂?
Lipids are organic molecules are nondiss
olvable in H2O
They are comprised of many C-H bonds
which store energy
Phospholipids,Glycerol,2 fatty acids,&
1 phosphate group (PO4)
磷脂的 结构?
细 胞膜的磷脂 双 分子 层结构脂肪酸命名
Fatty acids are designated by the total number
of carbon atoms:number of double bonds,follo
wed by the position of the dbl bond from the m
ethyl end of the molecule,indicated by w and a
number,or from the carboxyl end,indicated by
D.
– Example18:2w6 is an 18-C FA with 2 double bonds
beginning at the 6th C from the methyl end (same as
18:2D12).
The prefixes i and a indicate iso and anteiso br
anching,respectively,
– Example,i16:0 has a methyl branch on the first C fro
m the w end.
脂肪酸命名
-cy indicates a cyclopropane（ 环 丙 烷 ） fatty
acid
-Me indicates methyl branching from the car
boxyl end of the chain
– Example,10Me16:0 has a methyl branch on the
10th C from the carboxylic end.
The abbreviations t and c indicate trans and
cis configuration of the double bond
(cis is more common).
为 何使用脂肪酸特 别 是磷脂脂肪酸？
They are essential components of every living c
ell and are useful biomarkers because:
– they are and have great structural diversity and are c
oupled with high biological specificity.
Used as a proxy for the?living? and possibly the
active? microbial biomass
– The phosphate group is quickly consumed when an
organism dies
– They are not found in storage products
– Make up a relatively constant proportion of the biom
ass
PLFA 分析的意 义
Compare total PLFA pattern by multivariat
e statistics => changes in pattern = chan
ges in microbial community
Changes in specific PLFAs can be used a
s indicators of changes in specific organi
sm groups.
Baath,E,(2003) Microbial Ecology 45:373-383
方法
初提（ Initial Extraction）
脂肪分离（ Lipid Separation）
皂 化 /甲基化（ Saponification/Methylation）
GC分析（ GC analysis）
数 据分析和解 释 Data Analysis and Interpreta
tion
方法
初提（ Initial extraction）
– 1-25g soil (dw) is typically used
– Chloroform:Methanol:Phosphate buffer (2.0:1.
0:0.8)
– Centrifuge,filter,and remove chl phase
– Dry under N2
方法
脂肪酸分离（ Lipid Separation）
– Use solid-phase extraction silicic acid colum
ns
– Lipids separate by eluting with the following
chemicals,
Neutral lipids => with chloroform
Glycolipids => with acetone
Phospholipids => with methanol
方法
皂 化 /甲基化（ Saponification/Methylation）
Use 2M KOH dissolved in MeOH
气 相色 谱 分离脂肪酸甲脂
Separate FAMES on GC-FID (redissolve FAME wi
th hexane)
利用 标 准物确定峰高和出峰 时间
Use standards to determine quantitative amounts
and 37-FAME std to id peaks
多元 统计 分析 数 据
Use multivariate statistics to evaluate data (namel
y PCA or NMS)
Sample chromatograph
m in10 12,5 15 17,5 20 22,5 25 27,5 30
pA
20
40
60
80
100
120
F I D 1 A,(C,\ D O C U M E ~ 1\ J E N N \ M Y D O C U ~ 1\ R E SE AR C H \ G C -F I D ~ 1\ 0812 0312,D )
9.
881
10.
073
10.
536
11.
355
11.
897
12.
095
12.
393
12.
989
13.
158
13.
387
13.
491
13.
618
13.
727
13.
899
14.
132
14.
483
14.
736
14.
886
14.
941
15.
009
15.
072
15.
174
15.
419
15.
581
15.
677
15.
824
15.
925
16.
051
16.
146
16.
334
16.
421
16.
492
16.
881
17.
003
17.
073
17.
220
17.
291
17.
400
17.
622
17.
738
17.
807
17.
910
18.
130
18.
209
18.
320
18.
572
18.
875
18.
952
19.
019
19.
093
19.
192
19.
317
19.
483
19.
625
19.
765
19.
901
20.
006
20.
076
20.
370
20.
470
20.
627
20.
768
20.
880
21.
008
21.
063
21.
186
21.
314
21.
418
21.
515
21.
590
21.
671
21.
839
21.
972
22.
084
22.
243
22.
303
22.
364
22.
535
22.
657
22.
804
22.
933
23.
140
23.
210
23.
308
23.
410
23.
485
23.
590
23.
686
23.
800
23.
893
24.
050
24.
200
24.
321
24.
423
24.
496
24.
602
24.
662
24.
800
24.
872
24.
974
25.
152
25.
290
25.
545
25.
747
25.
972
26.
172
26.
272
26.
364
26.
480
26.
689
26.
912
27.
060
27.
247
27.
359
27.
464
27.
593
27.
895
28.
053
28.
230
28.
491
28.
658
28.
837
28.
942
29.
034
29.
131
29.
377
29.
443
29.
606
29.
863
m in14 16 18 20 22 24 26 28 30
pA
20
40
60
80
100
120
F I D 1 A,(C,\ D O C U M E ~ 1\ J E N N \ M Y D O C U ~ 1\ R E SE AR C H \ G C -F I D ~ 1\ 0812 0312,D )
15,0i
16,0
19,0 c y
18,2 w 6,9
18,1 w 9c
18,1 w 7c
15,0a
14,0
16,0 10 M e
12.
990
13.
161
13.
387
13.
618
13.
726
13.
899
14.
131
14.
480
14.
739
15.
009
15.
174
15.
418
15.
581
15.
677
15.
823
15.
926
16.
146
16.
492
16.
884
17.
003
17.
292
17.
399
17.
622
17.
736
17.
910
18.
127
18.
318
18.
569
18.
951
19.
093
19.
192
19.
317
19.
483
19.
623
19.
764
19.
901
20.
006
20.
076
20.
372
20.
468
20.
768
21.
062
21.
185
21.
311
21.
416
21.
513
21.
671
21.
838
21.
972
22.
365
22.
535
22.
804
22.
933
23.
141
23.
308
23.
408
23.
590
23.
686
23.
892
24.
049
24.
199
24.
321
24.
423
24.
496
24.
603
24.
872
25.
151
25.
289
25.
545
25.
751
25.
975
26.
171
26.
272
26.
361
26.
480
26.
689
26.
913
27.
064
27.
247
27.
359
27.
465
27.
594
27.
895
28.
052
28.
228
28.
490
28.
659
28.
837
28.
941
29.
035
29.
131
29.
376
29.
609
29.
863
18,0 10 M e
Sample Chromatograph
解 释脂肪酸 微生物 类 型
15:0i,17:0i,15:0a,etc.,Gram positive bacteria
cy17:0,cy19:0,18:1D11c Gram negative bacteria (als
o cy19:0 gm+)
10 Me18:0,10 Me17:0,10
Me16:0
Actinomycetes
18:2w6,9,18:1w9c Fungi
20:4 w6 Protozoan
16:1 w5 Arbuscular mycorrhizal fungi
18:1w8c Methanotrophs
解 释时 的注意事 项
A particular fatty acid might be misinterpreted
because its occurrence might be representativ
e of other organisms previously unknown
Therefore,it is important to know the fatty acid
composition of the individual species which m
ake up the community,
Can also evaluate using full,groups” of fatty a
cids instead of a signal signature
解 释
Sum the following PLFAs for bacterial bio
mass,i15:0,a15:0,i16:0,16:1w9,16:1w7
t,i17:0,a17:0,17:0,cy17:0,18:1w7 and
cy19:0
Use 18:2w6,9 and 18:1w9c for fungal bio
mass
Can use fungi:bacteria ratios
解 释
Cyclopropyl fatty acids(环 丙基脂肪酸 ) are
formed by a modification of existing mem
brane lipids,often as the organisms enter
the stationary phase.....it?s suggested tha
t this class of PLFAs is formed under stre
ssful conditions
16:1w7c and 18:1w7c are the precursors
to cy17:0 and cy19:0
PLFA Advantages
Detects microbial community in an environ
mental sample (i.e.,avoids problems asso
ciated with cultures and direct counting m
ethods)
Can be used to detect (rapid) changes in
a wide range of soil type,sediments,wate
r,and humus
Relatively easy and?quick? so large numbe
r of samples can be processed
PLFA 的 优 点
Provides more accurate and precise estimates
of the viable microbial biomass compared to C
FM.
PLFA profiles contain detailed info on lipid stru
cture that can be used to investigate microbial
community structure and metabolic condition.
Provides a fingerprint of microbial diversity at ti
me of sampling
Relatively inexpensive if you already own a GC
PLFA 的缺点
PLFA profiles do not reveal species-level infor
mation
Archae bacteria can not be determined with this
method
Can?t detect unusual FA or those found in low c
oncentrations => but these may represent a fun
ctionally,very important group
Interpretation needs further work as fatty acids i
n community structure can apply to more then
one group of organisms
PLFA 的缺点
Linking PLFA profiles and function of eco
systems has not been well established.
Spatial and temporal variability can be hig
h,thus,making interpretation difficult
Database is centered around fatty acids f
rom microorganisms from pure cultures
Size
shape
metabolic activity
nutrient requirement
oxygen requirement
habitats [temperature,pH,ionic concentrations]
形 态 多 样 性
Morphological characteristics in general are related to t
he way we visually perceive the features of an organis
m; its size and shape
From our perspectives,plants and animals have extensi
ve morphological diversity
For microbes,morphological diversity is limited
– Size and shape of cells
– Size and shape of colonies formed by bacteria
Morphological diversity is very limited for microbes
– There are probably millions of species of prokaryotes,and just
3 basic shapes of cells
– Colony morphology descriptions are also limited
Estimate thousands of species; how many colony types were obse
rved in lab?
生理多 样 性
What is the range of environmental parameters
under which organisms can survive?
Who lives where and under what conditions?
Consider physical/chemical parameters of the e
nvironment
– Temperature,light,O2,pH,pressure,etc.
Microbes have extensive physiological diversity
– They live in many environments uninhabitable by euk
aryotes
e.g,all of the above,plus deep subsurface rocks,pH 0 wat
ers,hot springs,antarctic ice fields,121°C water (250°F!)
微生物代 谢 多 样 性
Microbes have extensive metabolic diversity
– Photoautotrophy
Oxygenic photosynthesis AND anoxygenic photosynthesis
– Photoheterotrophy (not photosynthesis!)
Use light energy and organic compounds to make biomole
cules
Only Prokaryotes can do this!
– Chemoautotrophy
Use inorganic compounds for energy to fix CO2
– Several different compounds can be used
Only Prokaryotes can do this!
– Chemoheterotrophy
Use organic compounds for both carbon and energy
Often the same compound is used for both
Huge array of organic molecules are food for microbes,in
cluding many that are toxic or deadly to other organisms
遗传 多 样 性
True and heritable differences in genes (DNA
sequences) between organisms
Consider:
1,Morphological diversity
2,Physiological diversity
3,Metabolic diversity
4,Genetic diversity
1,2,3 can all be manifested at the genetic le
vel,and many times are
Genotypic differences (true genetic differences)
However,1,2,3 can also result from differen
t patterns of gene expression
Phenotypic differences (observable traits)
微生物多 样 性 评 价
从 多 个 方面
1,Morphological diversity
2,Physiological diversity
3,Metabolic diversity
4,Genetic diversity
需要多 种 新的方法形 态学评 价
Cell morphology
– Size and shape of cells
– Inclusions (e.g,endospores)
– Numbers and distribution of appendages
– Measured by light microscopy,e- microscopy
Special or differential stains (e.g,Gram stain) are often use
d
Colony morphology
– As done in lab exercise
Can characterize based on size,shape,color,outline,eleva
tion,refractility,other features
生理 学评 价
Examine biological parameters under a v
ariety of conditions
– Activity
– Growth (doubling time)
– Survival (persistence)
– Community diversity
Commonly assessed parameters:
– Temperature,pH,oxygen requirements,hal
otolerance,antibiotic/metal resistance
代 谢 和生化 评 价
Determine ranges of carbon sources used
Determine redox couples (electron donors
and acceptors) used for metabolism
Measure products formed
– CO2 evolution from aerobes
– Gases produced by fermenters
– Products from partial metabolism
– Toxic waste products
遗传 多 样 性 评 价
Generally use molecular techniques
– Phylogenetic analysis
– PCR/DGGE
Polymerase chain reaction/denaturing gradient gel electroph
oresis
– REP fingerprints
Molecular tools are providing more rapid and rel
iable means for measuring diversity and how it r
esponds to changing conditions
系 统发 生分析
The limited fossil record and structural simplicit
y of prokaryotes created great difficulties in de
veloping a classification of prokaryotes
A breakthrough came when Carl Woese and his
colleagues began to cluster prokaryotes into ta
xonomic groups based on comparisons of nucl
eic acid sequences
– Especially useful was the small-subunit ribosomal R
NA (SSU-rRNA) because all organisms have riboso
mes
Comparing sequences of these genes allows development
of a phylogenetic tree
Fig,27.13
Use conserved sequences to capture variable signat
ure sequences to establish a phylogeny of prokaryot
es and Eukaryotes; the,Tree of Life”
All three domains seem to have genomes that are chi
meric mixes of DNA transferred across the boundaries
of the domains.
This has lead some researchers to suggest replacing t
he classical tree with a web-like phylogeny
遗传 多 样 性分析 ——PCR-DGGE
采集土样 （ 3个重复,0.5g土 ）
DNA提取 （ DNA SPI试剂盒 ）
纯化 （ 用 FAST DNA PREP
SYSTEM清除蛋白质和其他杂质
） 获得 DNA模板顺向引物 27F(5’-
[6FAM]A GA GTTTGATCCTGGCTCA G-
3’) 和 反 向 引 物 338R(5’-
GCTGCCTCCCGTA GGA GT-3’)合成
0.06% 牛血 清白蛋 白,1.5mM MgCl2,2单位 Taq
DNA聚合酶,1× PCR缓冲液
ATP,TTP,
GTP,CTP
各 0.2 mM
10 ng 0.2 uM
94℃ 初始变性 3分钟
94℃ 变性 45秒
55℃ 退火 45秒
72℃ 延长 2分钟
25次
72℃ 保持 7分钟取 1ngPCR产物宽区聚丙烯酰氨凝胶电泳
PCR-DGGE基本步骤聚丙烯酰氨变性梯度凝胶电泳 条带分析建立系统树
DGGE
Denaturing Gradient Gel Electrophoresis
Separated DNA of same size based on se
quence differences.
Different sequences,behave differently at
different amounts of denaturing chemical
(or heat; see TGGE)
At some point DNA strand completely sep
arate.
Complete separation is hindered by GC-cl
amp added to one of the PCR primers.
Gradient Perpendicular to Electrop
horesis to Optimize Run
DGGE
Denaturing Gradient Gel
Electrophoresis (DGGE)
Urea/Formamide Gradient
Separates double stranded
DNA based on sequence
Muyzer et al.,1993
DGGE
Banding patterns are representative
of microbial community structure
Bands were excised
Eluted DNA was reamplified
using PCR
Band purity was verified with
DGGE
Sequencing and phylogenetic
analysis
Microbial Community Structure
of Hopane-Degrading Cultures
LC JI WS ET TC
Analysis of Bands Excised from DGGE
Profiles of Enrichments A and B
A B
ND
Alcaligenes sp,(.992)
P,azotoformans (.980)
Burkholderia cepacia (.997)
P,aeruginosa (.833)
Frateuria aurantia (.839)
ND
P,echinoides (.771)
Rhizobium/Brucella/
Ochrobactrum (.951)
Rhizobium sp,(.948)
ND
Commomonas sp,(.955)
ND
ND
P,rhodasiae (.927)
Alcaligenes sp,(.920)
ND
Burkholderia cepacia (.639)
P,alcaligenes (.696)
Strentophomonas sp,(.973)
P,echinoides (.808)
Sphingomonas sp,(.797)
Duganella zoogloides (.960)
Acetobacter sp,(.752)
Closest RDP Sequence (Sab) Closest RDP Sequence (Sab)
Phylogenetic Tree
Beta Subdivision
Burkholderia Group
Gamma Subdivision
Xanthomonas Group
Gamma Subdivision
Pseudomonas Group
Beta Subdivision
Acidovorax Group
Alpha Subdivision
Rhizobium Group
Alpha Subdivision
Sphingomonas Group
代 谢 多 样 性分析代 谢 多 样 性分析（功能多 样 性分析）
——碳 源利用方式分析（ BIOLOG分析）
BIOLOG自动微生物鉴定系统利用微生物对不同碳源利用率的差异，在大量研究基础上，设计筛选出 95种不同的碳源,检测细菌细胞利用不同碳源进行新陈代谢过程中产生的酶与四唑类物质（如 TTC,TV）
发生颜色反应和浊度差异为基础，运用显型排列技术检测出每种微生物的特征指纹图谱。在大量试验和数学模型基础上，
建立起指纹图谱与微生物种类相对应的数据库。 接种菌悬液到 96孔板后培养一定时间，通过仪器测定吸光度和浊度，与标准菌株数据库进行比对，得出最终鉴定结果。
原理方 法
称取 10g新鲜土置于 100 ml无菌水中，振荡 2
0分钟。用无菌水稀释到 10－ 3后，用 8通道加样器向 Biolog GN 微孔板 (Biolog,Inc.,Hay
ward,USA)各孔中分别添加 150 ul稀释后的悬液。每个土壤样品做 3个重复。 30℃ 恒温培养,48h后在 Emax自动读盘机上利用 Microlo
g Rel4.2软件读取 750 nm 和 590 nm波长下的光吸收，统计分析利用 SPSS10.0软件完成。
接种
将调整好浊度的菌悬液倾入 V型加样槽
采用 8通道移液器吸取菌悬液，添加 微孔鉴定板（ Microplate）
获取结果
将微孔板放入读数仪中读数，系统自动给出鉴定结果
0.000
0.200
0.400
0.600
0.800
1.000
1.200
0 50 100 150 200
培养时间（小时）
平均吸光值
（A
W
C
D
）
FACE-上
FACE-下
CK-上
CK-下多 样 性指 数 分析利用方式
use pattern AWCD
Shannon
index
Shannon
evenness Simpson index McIntosh index McIntosh Evenness
漏水型土露地蔬菜 PlOF 0.949(0.036)* 4.444(0.018) 0.982(0.002) 82.017(1.321) 9.961(0.298) 0.993(0.000)
漏水型土大棚蔬菜
PlPG
0.271
(0.019)
3.360
(0.027)
0.787
(0.028)
23.536
(0.216)
5.304
(0.354)
0.900
(0.011)
漏水型土稻麦轮作
PlRW
0.936
(0.057)
4.475
(0.017)
0.984
(0.001)
84.714
(1.510)
9.664
(0.504)
0.994
(0.000)
囊水型土露地蔬菜 WlOF 0.944(0.094) 4.415(0.031) 0.977(0.001) 79.075(2.741) 10.086(0.829) 0.991(0.001)
囊水型土大棚蔬菜 WlPG 0.164(0.012) 3.781(0.047) 0.835(0.006) 29.189(1.148) 2.883(0.204) 0.909(0.004)
爽水型土露地蔬菜
PmOF
0.991
(0.010)
4.436
(0.012)
0.975
(0.002)
79.824
(0.974)
10.546
(0.064)
0.990
(0.001)
爽水型土大棚蔬菜 PmPG 0.115(0.044) 2.768(0.771) 0.828(0.048) 14.000(10.733) 0.032(0.002) 0.849(0.053)
爽水型土稻麦轮作 PmRW 0.863(0.092) 4.422(0.027) 0.981(0.001) 80.194(1.832) 9.148(0.864) 0.993(0.000)
单一碳源利用方式典型变量因子载荷图
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
-0.
4
-0.
2
0 0.2 0.4 0.6 0.8 1 1.2
PlOF PlPG
PlRW WlOF
WlPG PmOF
PmPG PmRW
CV 1
CV2
土壤微生物群落 结构 多 样 性分析
——PLFA/FAME Analyses for
Microbial Community Assessm
ent
什 么 是磷脂?
Lipids are organic molecules are nondiss
olvable in H2O
They are comprised of many C-H bonds
which store energy
Phospholipids,Glycerol,2 fatty acids,&
1 phosphate group (PO4)
磷脂的 结构?
细 胞膜的磷脂 双 分子 层结构脂肪酸命名
Fatty acids are designated by the total number
of carbon atoms:number of double bonds,follo
wed by the position of the dbl bond from the m
ethyl end of the molecule,indicated by w and a
number,or from the carboxyl end,indicated by
D.
– Example18:2w6 is an 18-C FA with 2 double bonds
beginning at the 6th C from the methyl end (same as
18:2D12).
The prefixes i and a indicate iso and anteiso br
anching,respectively,
– Example,i16:0 has a methyl branch on the first C fro
m the w end.
脂肪酸命名
-cy indicates a cyclopropane（ 环 丙 烷 ） fatty
acid
-Me indicates methyl branching from the car
boxyl end of the chain
– Example,10Me16:0 has a methyl branch on the
10th C from the carboxylic end.
The abbreviations t and c indicate trans and
cis configuration of the double bond
(cis is more common).
为 何使用脂肪酸特 别 是磷脂脂肪酸？
They are essential components of every living c
ell and are useful biomarkers because:
– they are and have great structural diversity and are c
oupled with high biological specificity.
Used as a proxy for the?living? and possibly the
active? microbial biomass
– The phosphate group is quickly consumed when an
organism dies
– They are not found in storage products
– Make up a relatively constant proportion of the biom
ass
PLFA 分析的意 义
Compare total PLFA pattern by multivariat
e statistics => changes in pattern = chan
ges in microbial community
Changes in specific PLFAs can be used a
s indicators of changes in specific organi
sm groups.
Baath,E,(2003) Microbial Ecology 45:373-383
方法
初提（ Initial Extraction）
脂肪分离（ Lipid Separation）
皂 化 /甲基化（ Saponification/Methylation）
GC分析（ GC analysis）
数 据分析和解 释 Data Analysis and Interpreta
tion
方法
初提（ Initial extraction）
– 1-25g soil (dw) is typically used
– Chloroform:Methanol:Phosphate buffer (2.0:1.
0:0.8)
– Centrifuge,filter,and remove chl phase
– Dry under N2
方法
脂肪酸分离（ Lipid Separation）
– Use solid-phase extraction silicic acid colum
ns
– Lipids separate by eluting with the following
chemicals,
Neutral lipids => with chloroform
Glycolipids => with acetone
Phospholipids => with methanol
方法
皂 化 /甲基化（ Saponification/Methylation）
Use 2M KOH dissolved in MeOH
气 相色 谱 分离脂肪酸甲脂
Separate FAMES on GC-FID (redissolve FAME wi
th hexane)
利用 标 准物确定峰高和出峰 时间
Use standards to determine quantitative amounts
and 37-FAME std to id peaks
多元 统计 分析 数 据
Use multivariate statistics to evaluate data (namel
y PCA or NMS)
Sample chromatograph
m in10 12,5 15 17,5 20 22,5 25 27,5 30
pA
20
40
60
80
100
120
F I D 1 A,(C,\ D O C U M E ~ 1\ J E N N \ M Y D O C U ~ 1\ R E SE AR C H \ G C -F I D ~ 1\ 0812 0312,D )
9.
881
10.
073
10.
536
11.
355
11.
897
12.
095
12.
393
12.
989
13.
158
13.
387
13.
491
13.
618
13.
727
13.
899
14.
132
14.
483
14.
736
14.
886
14.
941
15.
009
15.
072
15.
174
15.
419
15.
581
15.
677
15.
824
15.
925
16.
051
16.
146
16.
334
16.
421
16.
492
16.
881
17.
003
17.
073
17.
220
17.
291
17.
400
17.
622
17.
738
17.
807
17.
910
18.
130
18.
209
18.
320
18.
572
18.
875
18.
952
19.
019
19.
093
19.
192
19.
317
19.
483
19.
625
19.
765
19.
901
20.
006
20.
076
20.
370
20.
470
20.
627
20.
768
20.
880
21.
008
21.
063
21.
186
21.
314
21.
418
21.
515
21.
590
21.
671
21.
839
21.
972
22.
084
22.
243
22.
303
22.
364
22.
535
22.
657
22.
804
22.
933
23.
140
23.
210
23.
308
23.
410
23.
485
23.
590
23.
686
23.
800
23.
893
24.
050
24.
200
24.
321
24.
423
24.
496
24.
602
24.
662
24.
800
24.
872
24.
974
25.
152
25.
290
25.
545
25.
747
25.
972
26.
172
26.
272
26.
364
26.
480
26.
689
26.
912
27.
060
27.
247
27.
359
27.
464
27.
593
27.
895
28.
053
28.
230
28.
491
28.
658
28.
837
28.
942
29.
034
29.
131
29.
377
29.
443
29.
606
29.
863
m in14 16 18 20 22 24 26 28 30
pA
20
40
60
80
100
120
F I D 1 A,(C,\ D O C U M E ~ 1\ J E N N \ M Y D O C U ~ 1\ R E SE AR C H \ G C -F I D ~ 1\ 0812 0312,D )
15,0i
16,0
19,0 c y
18,2 w 6,9
18,1 w 9c
18,1 w 7c
15,0a
14,0
16,0 10 M e
12.
990
13.
161
13.
387
13.
618
13.
726
13.
899
14.
131
14.
480
14.
739
15.
009
15.
174
15.
418
15.
581
15.
677
15.
823
15.
926
16.
146
16.
492
16.
884
17.
003
17.
292
17.
399
17.
622
17.
736
17.
910
18.
127
18.
318
18.
569
18.
951
19.
093
19.
192
19.
317
19.
483
19.
623
19.
764
19.
901
20.
006
20.
076
20.
372
20.
468
20.
768
21.
062
21.
185
21.
311
21.
416
21.
513
21.
671
21.
838
21.
972
22.
365
22.
535
22.
804
22.
933
23.
141
23.
308
23.
408
23.
590
23.
686
23.
892
24.
049
24.
199
24.
321
24.
423
24.
496
24.
603
24.
872
25.
151
25.
289
25.
545
25.
751
25.
975
26.
171
26.
272
26.
361
26.
480
26.
689
26.
913
27.
064
27.
247
27.
359
27.
465
27.
594
27.
895
28.
052
28.
228
28.
490
28.
659
28.
837
28.
941
29.
035
29.
131
29.
376
29.
609
29.
863
18,0 10 M e
Sample Chromatograph
解 释脂肪酸 微生物 类 型
15:0i,17:0i,15:0a,etc.,Gram positive bacteria
cy17:0,cy19:0,18:1D11c Gram negative bacteria (als
o cy19:0 gm+)
10 Me18:0,10 Me17:0,10
Me16:0
Actinomycetes
18:2w6,9,18:1w9c Fungi
20:4 w6 Protozoan
16:1 w5 Arbuscular mycorrhizal fungi
18:1w8c Methanotrophs
解 释时 的注意事 项
A particular fatty acid might be misinterpreted
because its occurrence might be representativ
e of other organisms previously unknown
Therefore,it is important to know the fatty acid
composition of the individual species which m
ake up the community,
Can also evaluate using full,groups” of fatty a
cids instead of a signal signature
解 释
Sum the following PLFAs for bacterial bio
mass,i15:0,a15:0,i16:0,16:1w9,16:1w7
t,i17:0,a17:0,17:0,cy17:0,18:1w7 and
cy19:0
Use 18:2w6,9 and 18:1w9c for fungal bio
mass
Can use fungi:bacteria ratios
解 释
Cyclopropyl fatty acids(环 丙基脂肪酸 ) are
formed by a modification of existing mem
brane lipids,often as the organisms enter
the stationary phase.....it?s suggested tha
t this class of PLFAs is formed under stre
ssful conditions
16:1w7c and 18:1w7c are the precursors
to cy17:0 and cy19:0
PLFA Advantages
Detects microbial community in an environ
mental sample (i.e.,avoids problems asso
ciated with cultures and direct counting m
ethods)
Can be used to detect (rapid) changes in
a wide range of soil type,sediments,wate
r,and humus
Relatively easy and?quick? so large numbe
r of samples can be processed
PLFA 的 优 点
Provides more accurate and precise estimates
of the viable microbial biomass compared to C
FM.
PLFA profiles contain detailed info on lipid stru
cture that can be used to investigate microbial
community structure and metabolic condition.
Provides a fingerprint of microbial diversity at ti
me of sampling
Relatively inexpensive if you already own a GC
PLFA 的缺点
PLFA profiles do not reveal species-level infor
mation
Archae bacteria can not be determined with this
method
Can?t detect unusual FA or those found in low c
oncentrations => but these may represent a fun
ctionally,very important group
Interpretation needs further work as fatty acids i
n community structure can apply to more then
one group of organisms
PLFA 的缺点
Linking PLFA profiles and function of eco
systems has not been well established.
Spatial and temporal variability can be hig
h,thus,making interpretation difficult
Database is centered around fatty acids f
rom microorganisms from pure cultures
