intrinsically disordered proteins in Archaea

21 Pages·2010·1.88 MB·English

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RESEARCH Open Access
Archaic chaos: intrinsically disordered proteins
in Archaea
Bin Xue1,2, Robert W Williams3, Christopher J Oldfield2,4, A Keith Dunker1,2, Vladimir N Uversky1,2,5*
From The ISIBM International Joint Conferences on Bioinformatics, Systems Biology and Intelligent
Computing (IJCBS)
Shanghai, China. 3-8 August 2009
Abstract
Background: Many proteins or their regions known as intrinsically disordered proteins (IDPs) and intrinsically
disordered regions (IDRs) lack unique 3D structure in their native states under physiological conditions yet fulfill key
biological functions. Earlier bioinformatics studies showed that IDPs and IDRs are highly abundant in different
proteomes and carry out mostly regulatory functions related to molecular recognition and signal transduction.
Archaea belong to an intriguing domain of life whose members, being microbes, are characterized by a unique
mosaic-like combination of bacterial and eukaryotic properties and include inhabitants of some of the most
extreme environments on the planet. With the expansion of the archaea genome data (more than fifty archaea
species from five different phyla are known now), and with recent improvements in the accuracy of intrinsic
disorder prediction, it is time to re-examine the abundance of IDPs and IDRs in the archaea domain.
Results: The abundance of IDPs and IDRs in 53 archaea species is analyzed. The amino acid composition profiles
of these species are generally quite different from each other. The disordered content is highly species-dependent.
Thermoproteales proteomes have 14% of disordered residues, while in Halobacteria, this value increases to 34%.
In proteomes of these two phyla, proteins containing long disordered regions account for 12% and 46%, whereas
4% and 26% their proteins are wholly disordered. These three measures of disorder content are linearly correlated
with each other at the genome level. There is a weak correlation between the environmental factors (such as
salinity, pH and temperature of the habitats) and the abundance of intrinsic disorder in Archaea, with various
environmental factors possessing different disorder-promoting strengths. Harsh environmental conditions, especially
those combining several hostile factors, clearly favor increased disorder content. Intrinsic disorder is highly
abundant in functional Pfam domains of the archaea origin. The analysis based on the disordered content and
phylogenetic tree indicated diverse evolution of intrinsic disorder among various classes and species of Archaea.
Conclusions: Archaea proteins are rich in intrinsic disorder. Some of these IDPs and IDRs likely evolve to help
archaea to accommodate to their hostile habitats. Other archaean IDPs and IDRs possess crucial biological
functions similar to those of the bacterial and eukaryotic IDPs/IDRs.
Introduction include single-celled microorganisms, prokaryotes.
Introducing Archaea Although archaea are similar to bacteria phenotypically
It is known that all the living systems on the Earth can (both have no cell nucleus or any other cellular orga-
be divided into three large domains, the Bacteria, the nelles inside their cells and are very often similar in size
Archaea, and the Eucarya, each containing at least two and shape), and despite a bacterial organization of
kingdoms [1-3]. The Bacteria and the Archaea domains archeae chromosome (messenger RNA with Shine-Dal-
garno sequences, genes assembled in operons, a single
origin of bidirectional replication), these two domains of
*Correspondence:[email protected]
1CenterforComputationalBiologyandBioinformatics,IndianaUniversity life are clearly different at the molecular level, and some
SchoolofMedicine,Indianapolis,IN46202,USA
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of the archaea genes, metabolic pathways and proteins ability to utilize a great variety of energy sources ranging
(especially ribosomal proteins and proteins involved in from sugars, to using ammonia, sulfur, metal ions and
transcriptions and translation) are more closely related even hydrogen gas as nutrients; some salt-tolerant
to those of eukaryotes [4-11]. For example, all eubacteria archaea (the Halobacteria) use sunlight as a source of
exhibit very similar subunit pattern in their RNA poly- energy; other archaea use CO in the atmosphere as a
2
merases (in terms of numbers and sizes), whereas this source of carbon via the carbon-fixation process, which
pattern is not related to that seen in the archaea or the is powered by inorganic sources of energy, rather than
eukaryotes [4], and several archaea and eukaryotic ribo- by capturing sunlight [19-21]. Many archaea are able to
somal protein homologues have no apparent counter- grow at temperatures above 100oC and are found in
part among the bacteria [5,6]. On the other hand, geysers, black smokers, and oil wells. The archaeon
archaea and eukaryotes are sufficiently dissimilar and Methanopyrus kandleri (Strain 116) can effectively grow
diverged early, and, therefore, they could not be placed at 122°C and high hydrostatic pressure (20 MPa), which
in a single domain of life either [1]. Generally speaking, is the highest recorded temperature at which an organ-
according to the detailed molecular analysis and com- ism will grow [22]. Others are found in very cold habi-
parative genomics, archaea are characterized by a com- tats and still others can survive in highly saline, acidic
bination of unique properties, such as left-handed (at pHs as low as 0, which is equivalent to 1.2 M sulfu-
isoprenoids containing glycerolipids, and mosaic bacter- ric acid), or alkaline water [23]. In addition to these
ial and eukaryotic features [12]. extremophiles (halophiles, hyperthermophiles, thermo-
Based on sequences of ribosomal RNAs, archaea were philes, psychrophiles, alkaliphiles, and acidophiles),
first classified as a separate group of prokaryotes in many archaea are mesophiles that grow in much milder
1977 [13]. Before that time prokaryotes were considered conditions, such as marshland, sewage, the oceans, and
as a single group. The term “archaea” was introduced in soils [24]. Although for a long time Archaea, in particu-
1987 to denote apparent primitive nature of correspond- lar Crenarchaeota, were considered ecologically insig-
ing organisms especially in comparison with the eukar- nificant, presuming to occupy mainly extreme and
yotes [2]. It is estimated that the total number of phyla unusual environments, it is becoming increasingly evi-
in the archaea domain range from 18 to 23, of which dent that previously unrecognized members of the
only 8 phyla have representatives that have been grown Archaea are abundant, globally distributed, and well-
in culture and studied directly [14]. In fact, most of the adapted to more pedestrian lifestyles and niches, includ-
culturable and well-investigated species of archaea ing symbiotic partnership with eukaryotic hosts [25].
belong to the two main phyla, Crenarchaeota, and Archaea are particularly numerous in the oceans, and
Euryarchaeota. Three new phyla, Thaumarchaeota, the archaea in plankton (as part of the picoplankton)
Nanoarchaeota, and Korarchaeota, were discovered may be one of the most abundant groups of organisms
very recently. Nanoarchaeota contains a nanosized on the planet, accounting for up to 40% of the bacterio-
symbiotic hyperthermophilic archaeon Nanoarchaeum plankton in deep ocean waters [26]. Therefore, it has
equitans from a submarine hot vent, which grows been pointed out that the study of archaea is essential
attached to the surface of a specific archaeal host, a new to understand the history of molecular mechanisms and
member of the genus Ignicoccus[15]. Based on the metabolism diversity and to unravel the mechanisms by
small subunit rRNA phylogeny it has been concluded which life can sustain in extreme environments [12].
that Korarchaeota comprises a group of microorgan-
isms that may have diverged early from the major Introducing intrinsically disordered proteins
archaeal phyla Crenarchaeota and Euryarchaeota, As verified by an increasing number of experimental
share many features of both of these main phyla, but are observations, more and more proteins or their regions
most closely related to the Crenarchaeota[16]. Mem- have been found to lack unique 3D structure in their
bers of the Thaumarchaeota phylum are mesophilic native states under physiological conditions. These
archaea which are different from hyperthermophilic regions and proteins, known as Intrinsically Disordered
Crenarchaeota to which they were originally ascribed Regions (IDR) or Intrinsically Disordered Proteins (IDP)
[17]. among different other names [27-30], present in solu-
It is recognized now that archaea are an important tion as conformational ensembles containing large num-
component of the biosphere [11], play important roles ber of widely different conformations that are in rapid
in the carbon and nitrogen cycle, and may contribute up interconversion on different time scales. The protein
to 20% of the total biomass on Earth [18]. The unique intrinsic disorder phenomenon is rapidly becoming well-
feature of some archaea is their ability to produce accepted in modern protein science. Unlike structured
methane gas in anaerobic environments; i.e., methano- proteins, IDPs stay as an ensemble of flexible conforma-
genesis. Another uniqueness of the archaea is their tions [27,31-33]. Although without stable 3D structures
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and in contradiction to the traditional sequence-struc- biological complexity, and that eukaryotes are highly
ture-function paradigm, IDPs play a number of crucial enriched in IDRs and IDPs, archaea may provide inter-
functional roles in living organisms, especially in vital esting information about the evolution of intrinsic
biological processes, such as signaling, recognition, and disorder.
regulation [27,31,32]. According to a statistical study on Previous studies discussed above provided very enligh-
SwissProt database, 238 out of 710 SwissProt functional tening information on the abundance of intrinsic disor-
keywords are strongly positively correlated with intrinsic der in archaea. However, at that time the number of
disorder, while another 302 functional keywords mostly species available for the bioinformatics analysis was
characterizing various catalytic activities are strongly rather limited. Studies utilizing PONDR®-VLXT, DIS-
negatively correlated with IDR [34]. OPRED2, and DisEMBL had only 7, 6, and 20 archaea
Due to their crucial functional roles, IDPs are highly species, respectively [39,40,42]. This limited number of
abundant in all species. According to computational species restricted the study on the phylogenetic relations
predictions by PONDR®-VLXT, typically 7-30% prokar- among the archaea species. Hence, with the expansion
yotic proteins contain long disordered regions of more of archaea genome data (more than fifty archaea species
than 30 consecutive residues, whereas in eukaryotes the from five different phyla are known now), it is necessary
amount of such proteins reaches 45-50% [28,35-38]. to re-examine the previous results and to explore new
Another estimation based on DISOPRED2 achieved information. Here, we systematically studied the abun-
similar results: around 2.0%, 4.2%, and 33.0% of proteins dance of intrinsic disorder in archaea and explored the
in archaea, bacteria, and eukaryota have long disordered functional and evolutionary roles of intrinsic disorder in
segments with 30 or more residues [39]. Higher con- this domain of life.
tents of long IDR were reported in a study using
another computational tool, DisEMBL [40]. In that Methods
study, 23~56%, 15~40%, and 25~78% of proteins in Datasets
archaea, bacteria, and eukaryota were predicted to have All protein sequences from the completed 53 archaea
IDR longer than 40 residues. In spite of the disagree- genome were downloaded from the ExPASy proteomics
ment between the reported values, the general trend server as of Jan. 2009 [43]. The taxonomy of these
among the three domains of life is quite consistent: at archaea is listed in Table S1 (see additional file 1). Note:
the proteome level, eukaryotes have much more disor- In the following discussion, names of phyla are in bold;
dered proteins than bacteria and archaea. This is a names of classes and orders are in bold italic; whereas
reflection of the vital roles of IDPs and IDRs in signaling names of species are in italic. All five known phyla of
and regulation. Furthermore, not only at proteome level, archaea are included in this study: Crenarchaeota and
but even in PDB, which is biased to structured proteins, Euryarchaeota have 15 and 32 species, respectively,
intrinsic disorder is also very abundant, and almost 70% each of the Thaumarchaeota and Nanoarchaeota phyla
of proteins in PDB have IDRs which are indicated by has two species; and finally there is only one species in
missing electron density [41]. the Korarchaeota phyla. All the species in Korarch-
Despite of the solid proofs of the relative abundance aeota, Thaumarchaeota, and Nanoarchaeota can be
of IDPs in nature, their origin is still a mystery. Where grouped into one class corresponding to that phylum.
are they coming from? How do they evolve? Although Although Crenarchaeota has 15 species, all of these
all of the three domains of life have a considerable species also belong to a single class, Thermoprotei.
amount of intrinsic disorder, modern species have Hence, these species could be combined together and be
evolved so effectively that ancient information is no analyzed as a single one. Euryarchaeota is the most
longer easy to retrieve. In this meaning, archaea could complicated phylum of archaea. It has 7 classes with
be an excellent candidate to tell the story of what hap- one to twelve species in each of them. In order to take
pened thousands of millions years ago. Since archaea this complexity into consideration, following analysis
are prokaryotes (they have no cell nucleus or any other will be conducted at three different levels: 5 phyla,
organelles within the cell), they seem to have appeared 11 classes, and 53 species.
early in the evolution. Furthermore, many archaea live
and grow at extreme conditions, such as high tempera- Disorder predictions
ture, which are believed to be very similar to the condi- In this study, two types of intrinsic disorder predictors
tions at the early time of planet formation. Finally, were utilized, per-residue predictors and binary classi-
archaea have genes and several metabolic pathways fiers. Per-residue predictors provide the distribution of
which are more similar to eukaryotes than bacteria. the propensity for intrinsic disorder over the amino acid
Hence, by taking into account the facts that eukaryotes sequence, whereas binary classifiers identify entire
need more signaling and regulation due to their protein as wholly ordered or wholly disordered. The
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per-residue predictors were used to generate two means PONDR®-VLXT is the first disorder predictor which was
for the evaluation of abundance of intrinsic disorder in designed by using neural networks. It is very sensitive to
a given protein, the total amount of disordered residues the changes of local compositional profile. One of its
and the number of long disordered regions containing prominent properties is the frequently occurring dips on
>30 consecutive amino acid residues predicted to be dis- the plot of disorder score (see Figure 1). These dips cor-
ordered. The binary classifiers were used to evaluate the respond to hydrophobic segments with the increased
number of wholly disordered proteins in a given propensity to order that are flanked by disordered
proteome. regions. many of these segments are found to be very
Per-residue disorder predictions important in molecular recognition, signaling and regu-
In this study, per-residue disorder predictors PONDR®- lation. They are now recognized as a Molecular Recog-
VLXT [36] and PONDR®-VSL2 [44] were utilized. nition Feature (MoRF) [38,45]. PONDR®-VSL2 is
Figure1ComparisonofdisorderpredictionbetweenPONDR-VLXTandPONDR-VSL2for(a)Q971E4and(b)Q9YC05:Thesolidline
isthedisorderscoreofPONDR-VLXT,whilethedashedlineisfromPONDR-VSL2.Thelineat(a)showsadipinVLXTpredictionwhileVSL2
predictsthelongsegmenttobedisordered.Thecirclein(b)representsalongdisorderedregionpredictedbyVLXT,butmissedbyVSL2.
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composed of a set of support vector machines and was the boundary are mostly disordered [37,42,46]. The dis-
trained on datasets containing disordered regions of var- tance of a curve from the CDF boundary can also be
ious lengths. It is one of the most accurate predictors used as a kind of measure of the disordered (structured)
developed so far. Both PONDR®-VLXT and VSL2 have status of a protein. This distance is further referred as
been applied in genome-wide studies on protein intrin- CDF-distance. Originally, CDF analysis was developed
sic disorder. The results of these analyses clearly indi- based on the results of the PONDR®-VLXT [28].
cated the existence of noticeable differences between Recently, other five CDF predictors were built using the
these two predictors. However, the sources of these dif- outputs of the PONDR®-VSL2 [44], PONDR®-VL3 [47],
ferences and their underlying biological significance IUPred [48], FoldIndex [49], and TopIDP [50]. Among
have not been clearly uncovered as of yet. Figure 1 these various CDFs, PONDR®-VSL2-CDF achieved the
represents the illustrative example of the disorder eva- highest accuracy, 5-10% higher than the accuracy of the
luation by PONDR®-VLXT and PONDR®-VSL2 predic- second best predictor [46].
tors in two unrelated proteins. This figure illustrates the Another method of measuring the disordered status of
typical feature of the PONDR®-VLXT plot which con- the entire protein is a Charge-Hydropathy (CH) plot
tains many sharp dips. As a result, long disordered [29]. CH-plot takes the averaged Kyte-Doolittle hydro-
regions are divided into a series of short disordered phobicity [51] and an absolute mean net charge of a
regions by these dips. Consequently, PONDR®-VLXT protein chain as the coordinates of the X- and Y-axis,
may under-estimate the ratio of long disordered regions respectively. This plot represents each protein as a sin-
as shown in Figure 1(a). On the other hand, although gle point in such a 2D graph. Since extended disordered
PONDR®-VSL2 is more accurate than PONDR®-VLXT proteins typically contain fewer hydrophobic residues
on short disordered/structured regions, it was also and more charged residues than ordered proteins, these
trained using a set of short protein segments. As a two types occupy different areas in the CH-phase dia-
result, for proteins that tend to have intersected disor- gram and can even be separated by a linear boundary
dered/structured segments, PONDR®-VSL2 may also [29]. According to this analysis, all of the proteins
have lower ratio for long disordered regions as indicated located above this boundary line are highly likely to be
by Figure 1(b). Hence, it would be beneficial to combine disordered, whereas proteins below this line are struc-
the results of several different predictors. However, in tured. On the CH-plot, the vertical distance from the
this study, due to reasons discussed above, we will focus location of a protein to the boundary line is then taken
on the results from the PONDR®-VSL2. as a scale of disorder (or structure) tendency of a pro-
Binary disorder classification tein. This distance is further referred as CH-distance.
Based on the per-residue disorder prediction, a Cumula- CDF- and CH-plots have different underlying princi-
tive Distribution Function (CDF) can be obtained to ples. The CDF-plot, being based on the disorder predic-
describe the disorder status of the entire protein tors of the PONDR® family, is strongly related to the
[37,42,46]. Basically, CDF is based on a cumulated histo- method of machine learning. Essentially, it is a statistical
gram of disordered residues at various disorder scores. analysis based on known structures in PDB. The CH
By definition, structured proteins will have more struc- measurement has a very intuitive physicochemical back-
tured residues and less disordered residues. Therefore, ground. Charged residues intend to interact with solvent
the CDF curve of a structured protein will increase very molecules, while hydrophobic residues prefer to avoid
quickly on the side of low disorder score, and then go contacts with solvent, therefore aggregating together.
flat on the side of high disorder score. On the other Hence, the CH-distance provides very important infor-
hand, for disordered proteins, the CDF curve will move mation about the general compactness and conforma-
upward slightly in regions of low disorder score, then tion of a polypeptide chain. By combining CDF- and
rapidly increase in the regions with high disorder scores. CH-distances in one graph, we have another method
Hence, on the 2D CDF plot, structured proteins tend to called the CH-CDF-plot [37,52]. On this plot, each
be located in the upper left half, whereas disordered point corresponds to a single protein and represents its
proteins are predominantly located at the lower right CDF-distance at the X-axis and the CH-distance at the
half of the plot. By comparing the locations of CDF Y-axis. CH>0 and CH<0 denote proteins predicted to be
curves for a group of fully disordered and fully struc- disordered and ordered by the CH-plot, respectively. On
tured proteins, a boundary line between these two the other hand, values of CDF>0 represent structured
groups of proteins can be identified. Then, this bound- proteins, and CDF<0 correspond to disordered proteins.
ary can be used to classify any given protein as wholly Hence, the entire field can be divided into four quad-
ordered or wholly disordered. Proteins whose CDF rants by cutting lines CH=0 and CDF=0. Lower right
curves are above the boundary line are mostly struc- quadrant corresponds to proteins predicted to be struc-
tured, whereas proteins with CDF curves located below tured by both CH and CDF, whereas upper left
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quadrant contains proteins predicted to be is disordered
6000
by both methods.
( a )
(2.1) (2.3) (2.5) (2.7)
(4)
Composition profiling 5000 (2.2) (2.4) (2.6) (2.8)
To gain insight into the relationships between sequence (1) (3)(5)
No. of Proteins
and disorder, the amino acid compositions of Archaea
s 4000 Taxonomy
n
proteomes were compared using an approach developed i
e
for the analysis of intrinsically disordered proteins ot
Pr 3000
[28,53]. To this end, the fractional difference in compo- f
sition between a given protein set (an Archaean pro- o. o
teome), and proteins from the Fully Disordered Dataset N 2000
(FDD) [46,54] was calculated for each amino acid resi-
dues as described in [28,53]. The fractional difference
1000
was calculated as (C -C )/C , where C is the con-
X FDD FDD X
tent of a given amino acid in a given proteome, and
0
C is the corresponding content in FDD proteins.
FDD
These fractional differences for each proteome are then 0 10 20 30 40 50
plotted for each amino acid. This analysis was per- Species
formed using a Composition Profiler, a computational
Figure 2 Size of proteome of each species: The X-axis is the
tool that automates this task and graphically summarizes indexofthenumberofeachspecies,whiletheY-axisisthe
the results [53]. Composition Profiler is available at numberofproteins.Filledcirclesrepresentthesizeoftheproteome
http://profiler.cs.ucr.edu. ofeachspecies.Filledsquaresindicatethetaxonomyofarchaea
withsimilarspeciestogetherandonsamelevel.(1),(3)-(5)indicate
speciesinfourphyla:Crenarchaeota,Korarchaeota,
Results and discussion
Nanoarcgaeota,andThaumarchaeota.(2.1)-(2.8)areeight
Major characteristics of the Archaea proteomes differentclassesinthephylumofEuryarchaeotaasshownin
Archaea are very abundant in nature, play a number of Table.1.
important roles in the cycle of carbon and nitrogen on
earth [18]. Although most of archaea live in ocean,
many of these microbes are extremophiles since they species. After this division is taken into account, the
live, grow and prosper in extremely harsh environ- trends in the proteome sizes of these 15 species became
ments, such environments of highly salty lakes or hot/ obvious. Figure 2 shows that the members of the Desul-
boiling springs. For the cells of “normal” organisms furococcales order are relatively uniform and have the
(e.g., mammals), these types of environment are abso- smallest proteomes size in this phylum. Two other
lutely lethal, since high temperatures or high salt con- orders (Sulfolobales and Thermoproteales) still possess
centrations will inevitably denature proteins of these large variability in their proteome sizes. In Euryarch-
organisms, invalidate their functions, and terminate aeota, as shown by taxonomy (2.1) – (2.7) and corre-
crucial biological pathways, eventually leading to the sponding proteome size in Figure 2, Halobacteria has
cell death. However, compared to these normal cells, the largest proteomes; Methanococci and Thermococci
archaea developed special mechanisms to counteract have fewer proteins in their proteomes; whereas Metha-
the harmful influence of these environments. The nomicrobia have the largest fluctuations in proteome
major components involved in these protective size among various species. Apparently, all the species
mechanisms should directly target the most abundant with small proteomes are characterized by a globule-like
bio-substance: proteins. Therefore, the comparative morphology. The relatively large number of proteins in
analysis of proteomes of various species living at var- Halobacteria is also expected, since extra proteins may
ious habitats should provide crucial information on the be needed to help these species deal with the high con-
similarities and differences of these organisms and on centrations of ions in their environment. Finally, Uncul-
the mechanisms of the adaptation. tured methanogenic archaeon which belong to the
Figure 2 presents the size distribution of proteomes of Euryarchaeota phylum has more than 3000 proteins
various archaea species analyzed in this study. Although and ranks as one of the largest proteomes in Archaea.
15 species in the first phylum, Crenarchaeota, belong Korarchaeota and Thaumarchaeota have middle-sized
to the same class, they can be divided into three orders: proteomes. Nanoarchaeota have the only representative
the first order is Desulfurococcales with 4 species; the Nanoarchaeum equitans, which is the simplest species
second order is Sulfolobales having another 4 species; in Archaea being characterized by the smallest proteome
and the last order is Thermoproteales which contains 7 and having only 536 proteins.
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20
18 Crenarchaeota
Euryarchaeota
16 Korarchaeota
Nanoarchaeota
14 Thaumarchaeota
ge 12
a
t
n 10
e
c
r
e 8
P
6
4
2
( a )
0
0 250 500 750 1000 1250 1500
Length
18
Archaeoglobi
16 Halobacteria
Methanococci
14 Methanomicrobia
Methanopyri
12 Thermococci
e Thermoplasmata
ag 10 UNCMA
t
n
e
c 8
r
e
P
6
4
2
( b )
0
0 250 500 750 1000 1250 1500
Length
Figure3Lengthdistributionofproteinsinfivephyla(a) andeightclasses(b)ofEuryarchaeota.X-axis:“X”lengthofprotein;Y-axis:
percentageofproteinswith“X”length.Theupperlimitofthex-axisistakenas1500residuesforvisualizationpurposes.However,therearestill
scattereddistributionsofproteinsbeyondthisuplimit.
Not only the size of proteome is important, but also law distribution. All of the species have less than 2%
the size of proteins in each genome. The length dis- extremely short proteins (less than 50aa). The most
tributions for 5 phyla and 7 classes of Euryarchaeota optimal protein length for all species is around 100 –
phylum are shown in Figure 3(a) and Figure 3(b), 200 residues. Proteins with these lengths constitute
respectively. Clearly, in general, distributions of protein approximately 25% of any given proteome. Larger pro-
length among all the species are very similar, although teins are also very common in all the species: the con-
some important subtle differences can be found. The tent of proteins longer than 500aa is around 10% or
general shape of the distribution is similar to the power- even higher. Very long proteins (longer than 1000 aa)
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are not very common and account for several percent, residues. In Methanococci, the content of proteins with
comparable to the proportion of the extremely short 50 – 450 residues is always the highest.
proteins. As shown in Figure 3(a), Thaumarchaeota
and Korarchaeota have fewer extremely short and short Amino acid compositions of the Archaea proteomes
proteins. However, the members of the Korarchaeota At the next stage, the amino acid compositions of pro-
phylum have more middle-sized proteins (150 – 250aa), teins from various Archaea were analyzed. The results
whereas Thaumarchaeota have more proteins with of this analysis are shown in Figure 4 as the relative
250 – 500 residues. In addition, Nanoarchaeota has composition profiles calculated for various species as
around 5% percent more middle-sized proteins with described by Vacic and colleagues [53]. Here, the frac-
50 – 100 residues. In Figure 3(b), Archaeoglobi and tional difference in composition between a given protein
Halobacteria have around 4 times more extremely set and a set of completely disordered proteins was cal-
short proteins than the other 5 classes. The other 5 culated for each amino acid residue. The fractional dif-
classes are enriched in longer proteins with 250 – 450 ference was evaluated as (C -C )/C , where C is
X FDD FDD X
2.0 ( a )
Crenarchaeota
Euryarchaeota
Korarchaeota
1.5 Nanoarchaeota
D Thermarchaeota
D
CF
) / 1.0
D
D
CF
0.5
-
CDataset 0.0
(
-0.5
-1.0
W C F I Y V L H M A T R G Q S N P D E K
Residue
2.0 ( b ) Archaeoglobi
Halobacteria
Mathanococci
1.5 Methanomicrobia
D Methanopyri
CFD Thermococci
) / 1.0 TUhNeCrmMoAplasmata
D
D
CF
0.5
-
CDataset 0.0
(
-0.5
-1.0
W C F I Y V L H M A T R G Q S N P D E K
Residue
Figure 4 Composition profile of amino acids for (a) five phyla, and (b) eight classes in Euryarchaeota: Residues on the X-axis are
arrangedaccordingtotheincreasingdisordertendency.Y-axis:therelativecompositionalprofilecomparedtoafullydisordereddataset.
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the content of a given amino acid in a given protein set, and a noticeable decrease in (H, A, and R). Methano-
and C is the corresponding content in the Fully Dis- pyri show a very large increase in V, and R, and a
FDD
ordered Dataset (FDD) [46,54]. The usefulness of this decrease in S, N, and K. Thermoplasmata have much
analysis is determined by the fact that the propensity of more I, Y, and M than other classes.
a given protein to be intrinsically disordered is deter- Table 1 presents the averaged Kullback-Leibler
mined by a set of specific features of its amino acid [54,56,57] divergence among all the phyla and classes.
sequence and composition [28,29,50,53,55]. For example, As stated in our previous study, values below 0.01 corre-
intrinsically disordered proteins are significantly spond to high similarities between two datasets; values
depleted in bulky hydrophobic (I, L, and V) and aro- between 0.01 and 0.05 indicate a gray zone; values larger
matic amino acid residues (W, Y, and F), which would than 0.05 correspond to the datasets which are unlikely
normally form the hydrophobic core of a folded globular to be similar; and values greater than 0.1 correspond to
protein, and also possess a low content of C and N resi- the non-similar datasets [54]. This Table provides a very
dues. These depleted residues, I, L, V, W, F, Y, C and straightforward description of the similarity among the
N, were proposed to be called order-promoting amino various Archaea species and shows that several species
acids. On the other hand, intrinsically disordered pro- are similar to each other in terms of their amino acid
teins and regions were shown to be substantially compositions.
enriched in disorder-promoting amino acids: E, K, R, G,
Q, S, P and A. Disorder distribution in the Archaea proteomes
Application of this tool to the analysis of the Archaea The differences in the protein length distributions
proteomes revealed a number of interesting features. among the proteomes of various Archaea and in their
Figure 4(a) clearly shows that all 5 phyla contain many amino acid compositions lead to another important
more structure-promoting residues (W, C, F, I, Y, V, L) question: Is intrinsic disorder distributed evenly in all
and fewer disorder-promoting residues (Q, S, P, E, K) these species or not? The comparison of various disor-
than the FDD proteins. In Figure 4(a), the content of F, der contents among 53 species is shown in Figure 5,
I, Q, P, E, and K are rather consistent between the 5 where the amount of disorder in different Archea pro-
phyla, where compared to FDD isoleucine had the high- teomes is annotated as the percentage of predicted dis-
est abundance in all 5 phyla. By comparing each phy- ordered residues (Figure 5(a)), the amount of long
lum, Crenarchaeota and Korarchaeota have more disordered regions (Figure 5(b)), and the amount of
similarity with each other. They both have a low content wholly disordered proteins (Figure 5(c)). Figure 5 clearly
of cystein, but are rich in tryptophan. In comparison shows that Crenarchaeota have a relatively lower con-
with other phyla, they are also very similar in their con- tent of disorder than the other four phyla. On the other
tent of H, T, R, and D. Figure 4(b) shows that the con- hand, Korarchaeota have the highest disorder content.
tents of L, Q, S, and P are stable among various classes In Euryarchaeota, the ratios diverged: Halobacteria
of Euryarchaeota. Halobacteria are very special due to have much higher disorder content than other species
their low content of structure-promoting residues (C, F, and Thermococci have the lowest disorder content.
I, and Y), abnormally large increments in A, T, R, G, These observations indicated the influence of environ-
and D, and a dramatic decrease in K abundance. ment on the abundance of intrinsic disorder in a given
Methanococci show a large increase in (I, N, and K) organism. Halobacteria need to be more adaptive in
Table 1Kullback-Leibler (KL)distances among 12classes of5archaeaphyla
(1) (2.1) (2.2) (2.3) (2.4) (2.5) (2.6) (2.7) (2.8) (3) (4) (5)
(1) 1 0.012 0.091 0.065 0.019 0.049 0.012 0.041 0.016 0.015 0.076 0.027
(2.1) 1 0.107 0.046 0.017 0.051 0.008 0.042 0.022 0.016 0.068 0.026
(2.2) 1 0.214 0.088 0.059 0.135 0.158 0.068 0.110 0.271 0.074
(2.3) 1 0.034 0.170 0.040 0.028 0.062 0.070 0.022 0.052
(2.4) 1 0.078 0.023 0.022 0.007 0.026 0.065 0.005
(2.5) 1 0.071 0.147 0.065 0.055 0.200 0.079
(2.6) 1 0.035 0.032 0.018 0.044 0.035
(2.7) 1 0.036 0.041 0.048 0.030
(2.8) 1 0.029 0.094 0.006
(3) 1 0.089 0.032
(4) 1 0.091
(5) 1
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( a ) ( c )
(2.1) (2.3) (2.5) (2.7) (2.1) (2.3) (2.5) (2.7)
0.5 0.4
(4) (4)
(2.2) (2.4) (2.6) (2.8) (2.2) (2.4) (2.6) (2.8)
(1) (3)(5) (1) (3)(5)
0.4 Ratio of Disordered Residues 0.3 Ratio of Fully IDP
ge Taxonomy ge Taxonomy
a a
t t
n n
e e
c 0.3 c 0.2
r r
e e
P P
0.2 0.1
0.1 0.0
0 10 20 30 40 50 0 10 20 30 40 50
Species Species
0.5
( b ) ( d )
0.7 (2.1) (2.3) (2.5) (2.7) Long IDR vs IDAA
Fully IDP vs IDAA
(4)
0.6 (2.2) (2.4) (2.6) (2.8) 0.4
(1) (3)(5)
0.5 Ratio of Long IDR (>30aa)
ge Taxonomy ge 0.3
a a Y = -0.11 + 1.68X
nt 0.4 nt
e e
c c
r r
e 0.3 e 0.2
P P
0.2
Y = -0.12 + 1.07X
0.1
0.1
0.0 0.0
0 10 20 30 40 50 0.0 0.1 0.2 0.3 0.4 0.5
Species Percentage of Disordered Residues (IDAA%)
Figure5Variousmeasuresofintrinsicdisordercontentin53species:(a),Ratioofdisorderedresiduesineachspecies;(b),Percentageof
proteinswithlongdisorderedregions(>30aa)ineachspecies;(c),Ratiooffullydisorderedproteinsineachspecies.Inallfiguresabove,the
X-axisistheindexnumberofeachspecies.Filledsquaresindicatethetaxonomyofarchaeawithsimilarspeciestogetherandonthesamelevel.
(1),(3)-(5)indicatespeciesinfourphyla:Crenarchaeota,Korarchaeota,Nanoarcgaeota,andThaumarchaeota.(2.1)-(2.8)areeightdifferent
classesinthephylumofEuryarchaeota.(d),Correlationamongvariousdisorderedcontents.X-axis:theratioofdisorderedresidues.Y-axis:
percentageofproteinswithlongdisorderedregionsandpercentageoffullydisorderedproteins,accordingly.
signaling and regulation to counteract the high ion con- well-correlated at the proteome level. In other words,
centration. Thermococci tend to have more stable this analysis clearly shows that the proteomes with the
ordered proteins to resist the influence of high environ- larger total amount of disordered residues typically con-
ment temperature. tain a larger amount of long disordered regions and lar-
Figure 5(d) represents the relation among the various ger number of wholly disordered proteins.
means used to evaluate the disorder content in the To better understand the distribution of wholly disor-
Archaea proteomes. As shown by this plot, the total dered proteins in various Archaea proteomes, we further
number of disordered residues, the amount of long analyzed their CH-CDF phase space. The averaged data
IDRs, and the number of wholly disordered IDPs are for all 5 Archaea phyla and 8 classes of Euryarchaeota