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Prioritizing orphan proteins for further study
using phylogenomics and gene expression
profiles in Streptomyces coelicolor
Alam et al.
Alam et al. BMC Research Notes 2011, 4:325
http://www.biomedcentral.com/1756-0500/4/325 (7 September 2011)

Alam et al. BMC Research Notes 2011, 4:325
http://www.biomedcentral.com/1756-0500/4/325

RESEARCH ARTICLE

Open Access

Prioritizing orphan proteins for further study
using phylogenomics and gene expression
profiles in Streptomyces coelicolor
Mohammad Tauqeer Alam1,2, Eriko Takano3 and Rainer Breitling1,2*

Abstract
Background: Streptomyces coelicolor, a model organism of antibiotic producing bacteria, has one of the largest
genomes of the bacterial kingdom, including 7825 predicted protein coding genes. A large number of these
genes, nearly 34%, are functionally orphan (hypothetical proteins with unknown function). However, in gene
expression time course data, many of these functionally orphan genes show interesting expression patterns.
Results: In this paper, we analyzed all functionally orphan genes of Streptomyces coelicolor and identified a list of
“high priority” orphans by combining gene expression analysis and additional phylogenetic information (i.e. the
level of evolutionary conservation of each protein).
Conclusions: The prioritized orphan genes are promising candidates to be examined experimentally in the lab for
further characterization of their function.

Background
Here we present an analysis of orphan genes (hypothetical genes with unknown function) in the Streptomyces
coelicolor genome, combining gene expression analysis
and comparative genomics. The aim is to prioritize
orphan genes for further study. In our gene expression
studies [1,2], we frequently encountered genes that
showed interesting expression patterns, but had no
known function. To identify which of these genes merit
in-depth experimental analysis, we developed a strategy
for prioritizing protein encoding genes for additional
characterization, combining phylogenomic information
[3] (i.e. the level of evolutionary conservation of each
protein), and gene expression data from a large gene
expression time series [1]. We postulate that widely conserved proteins that show a physiologically relevant
dynamic expression pattern are the most promising candidates for further experimental study, e.g. using gene
overexpression and knock-out or knock-down
approaches.
* Correspondence: rainer.breitling@glasgow.ac.uk
1
Institute of Molecular, Cell and Systems Biology College of Medical,
Veterinary and Life Sciences, Joseph Black Building B3.10, University of
Glasgow, G12 8QQ, Glasgow, UK
Full list of author information is available at the end of the article

The functional annotation of orphan genes is not only
relevant for its basic biological interest, but is also an
important help for the improvement of genome-scale
metabolic models based on genome annotation. These
models in their initial form almost always contain gaps
that need to be filled by manual curation or automated
gap-filling algorithms that add missing essential metabolic activities to the models [2,4-7].
During our previous studies of genome-scale metabolic models of Streptomyces coelicolor and its relatives, we regularly had to postulate enzymatic
functions that had not been assigned to specific proteins in the organisms [2,7]. Assigning specific
enzyme-coding genes to these orphan metabolic activities is very important for the subsequent analysis and
interpretation of the models, and several approaches
have been developed to assign sequences to the orphan
metabolic activities: they employ, for example, mRNA
co-expression analysis [8], phylogenetic profile information [9-11], pattern recognition techniques [12] or
comparative genomics [13]. These approaches are
organism specific and have mostly been employed for
well-studied model organisms such as Escherichia coli
and Saccharomyces cerevisiae.

© 2011 Breitling et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in
any medium, provided the original work is properly cited.

Alam et al. BMC Research Notes 2011, 4:325
http://www.biomedcentral.com/1756-0500/4/325

Results and discussion
Of the 7825 predicted protein coding genes in the Streptomyces coelicolor genome [14], according to a re-annotation of the genome sequence in 2009, 2688 (34%) are
coding for functionally orphan proteins, i.e. proteins
that are annotated as “hypothetical protein”, “conserved
protein”, “putative membrane protein” or “putative
secreted protein”. Of these orphan proteins, 26 are conserved in all and 381 are present in at least half (22/44)
of the 44 analyzed complete actinomycete genomes (see
Methods section for a complete species list). 683 orphan
proteins are present in at least 11 (25%) and 177 are
conserved in at least 33 (75%) actinomycete genomes.
Of the 381 generally conserved actinomycete orphan
proteins (i.e., those that are present in at least half of
the analyzed genomes), 25 are also encoded in all species in a selected set of diverse non-actinomycete bacterial genomes (Bacillus subtilis, Escherichia coli K12,
Lactobacillus plantarum WCFS1, Staphylococcus aureus,
and Streptococcus pneumonia AP200), and 73 are present in at least three of the representative bacterial genomes (see Additional File 1: Supplementary Table 1.xls).
Of these 73 ultra-highly conserved bacterial orphan
genes, 22 also have putative homologues (reciprocal best
BLAST hits) in at least half of the species in a representative set of eight non-bacterial genomes (the eukaryotes
Caenorhabditis elegans, Arabidopsis thaliana, Plasmodium falciparum, Drosophila melanogaster, Saccharomyces cerevisiae and Homo sapiens, and the archaea
Haloterrigena turkmenica and Methanosarcina acetivorans). These proteins are therefore almost universally
conserved; however, although there seems to be significant conservation of some orphan proteins, none of
them is truly universal, i.e. none has a putative homologue in all of the 58 studied genomes. This is most likely
due to the fact that some of the included actinomycete
genomes are highly reduced, as a result of the parasitic
lifestyle of the organism, and the large phylogenetic distance covered (with the corresponding major differences
in basic physiological processes).
To prioritize the orphan proteins for further characterization, we therefore summarized the phylogenomic
information (i.e. the level of evolutionary conservation
of each protein) in a single “conservation” score, which
expresses the degree of conservation across the three
domains examined (actinomycetes, non-actinomycete
bacteria, non-bacteria). This score was combined with a
second measure of expression dynamics across a large
gene expression time series studying the metabolic
switch caused by phosphate starvation. In this experiment, a fermenter culture of S. coelicolor was grown in
phosphate-limited conditions, and gene expression data
were obtained at 32 finely spaced time points

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throughout the duration of the experiment. Phosphate
was depleted after about 35 hours, triggering a metabolic switch from primary to secondary metabolism,
accompanied by a rapid global reorganization of the
transcriptome, involving genes with a wide range of biological functions, from central metabolism and antibiotic
biosynthesis, to cellular development and maintenance
[1]. The “expression dynamics” score described in the
Methods section identifies genes that show a smooth
expression trend across (part of) the time series and
favors those genes that show a particularly strong (steplike) expression change at one time point. This is
intended to allow to focus on genes that are not only
passively following the expression change during nutrient depletion but that show evidence for active regulation, which is indicative of a central function in cellular
physiology. Based on the p-value of the “expression
dynamics” score, we assigned a rank to each gene, and
averaged this value with the rank of the “conservation”
score. 734 orphan genes are significantly up- or downregulated with expression dynamic p-values less than
0.00001 (significant after multiple-testing correction).
Using the averaged conservation and expression
dynamics rank, we arrived at a list of 30 top orphan proteins. These were examined in more detail to determine
if their function was really unknown: we checked the
most recent versions of the Uniprot [15] and StrepDB
database for annotations, performed a PSI-BLAST
against the Uniprot database, compared the annotation
of the homologs in E. coli, yeast and human where these
were available, and analyzed the domain architecture
using SMART tool (Simple Modular Architecture
Research Tool) [16]. Using this information, we asked
three microbiologist and bioinformaticians to independently score the genes according to their “orphanicity”, i.
e. their confidence in the absence of a known potential
function. The three raters used a large collection of automatically provided evidence for all candidate genes,
including annotation from the most recent versions of
the Uniprot and StrepDB database, output of a PSIBLAST against the Uniprot database, and the output of a
domain architecture analysis using the SMART tool
(Simple Modular Architecture Research Tool). In addition, they were free to do their own literature research
and sequence analysis, although this did not generally
identify useful extra information. The average score of
the three raters was combined with the average score of
the conservation and expression dynamics to arrive at a
final ranking for the most interesting orphan genes for
further study: the top genes are those for which we have
absolutely no information about their function, that are
ultra-highly conserved across species, and show a highly
significant dynamics in their gene expression (Table 1).

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Table 1 Top 30 orphan proteins for further study
Gene Name

Annotation

Final rank

Orphanicity rank

Exp. quantile

p-value

act

bac

non-bac

SCO1521

hypothetical protein

1

1

0.21

3.71E-10

44

5

5

SCO2301

hypothetical protein

6

4

0.34

3.27E-07

43

5

5

SCO5362

hypothetical protein

6.5

9

0.13

2.02E-07

44

4

7

SCO1769

hypothetical protein

8

5

0.12

3.08E-08

40

3

1

SCO5746

hypothetical protein

8

7

0.18

4.38E-18

20

3

1

SCO3882

hypothetical protein

8.5

2

0.18

6.71E-08

38

5

1

SCO5546

hypothetical protein

8.5

14

0.35

7.62E-09

42

3

6

SCO5745

hypothetical protein

9.5

17

0.02

9.49E-10

43

4

6

SCO1925

hypothetical protein

11.5

18

0.09

1.24E-07

44

5

3

SCO2577

hypothetical protein

12

3

0.64

2.66E-07

41

5

1

SCO1676

hypothetical protein

12.5

15

0.32

7.05E-09

31

1

4

SCO1919

hypothetical protein

12.5

11

0.16

5.74E-07

44

4

2

SCO5491

hypothetical protein

12.5

6

0.35

3.07E-07

32

3

3

SCO2081

hypothetical protein

13

8

0.60

2.88E-08

38

2

1

SCO2902

hypothetical protein

14.5

22

0.37

3.05E-07

43

5

4

SCO1522

hypothetical protein

15.5

19

0.19

6.47E-07

43

3

5

SCO1920

hypothetical protein

16

12

0.27

1.71E-06

42

5

5

SCO3839

hypothetical protein

16.5

27

0.35

1.60E-08

35

3

2

SCO3960

hypothetical protein

17.5

13

0.30

5.66E-08

29

5

1

SCO2901

hypothetical protein

18

23

0.36

5.37E-07

41

3

5

SCO1924

hypothetical protein

18.5

20

0.08

6.81E-08

44

1

2

SCO6766

hypothetical protein

18.5

10

0.19

4.55E-08

20

1

2

SCO1775

hypothetical protein

21

16

0.32

3.00E-06

42

4

2

SCO1222

hypothetical protein

22

21

0.43

3.33E-09

27

1

1

SCO5645

hypothetical protein

22

28

0.07

3.11E-07

36

4

2

SCO1530

hypothetical protein

24.5

24

0.03

8.99E-07

43

1

5

SCO2497

hypothetical protein

26.5

29

0.52

2.38E-06

37

5

7

SCO5787

hypothetical protein

27

26

0.12

5.88E-06

44

3

7

SCO2599

hypothetical protein

27.5

25

0.13

4.17E-07

44

1

1

SCO5711

hypothetical protein

29.5

30

0.12

8.65E-06

44

5

5

The proteins are prioritized according to their conservation across actinomycetes, bacteria and non-bacteria; their expression dynamics (summarized in the pvalue); and their orphanicity, i.e. the absence of any functional information, assessed as described in the text.

Based on the gene expression profiles (Figure 1), the
candidate genes SCO5746 and SCO1222 are particularly
interesting: they show a very strong switch upon phosphate starvation, and their expression increases in stationary phase similar to the expression pattern of the
antibiotic biosynthesis gene clusters act and red. All other
genes show a decrease of expression along the time
course. SCO5746 has a putative uncharacterized homolog
in E. coli and contains a domain of the DegT/DnrJ/EryC1/
StrS aminotransferase family. The aminotransferase activity was demonstrated for purified StsC protein, which acts
as an L-glutamine:scyllo-inosose aminotransferase and catalyses the first amino acid transfer in the biosynthesis of
the streptidine subunit of antibiotic streptomycin. It is
therefore tempting to speculate that the SCO5746 gene

has some role in the biosynthesis of a new antibiotic in S.
coelicolor as well, and the same might be the case for the
completely uncharacterized SCO1222. The closest putative
antibiotic biosynthesis clusters are SCO5799-SCO5801
(siderophore synthetase type) and SCO1206-SCO1208
(chalcone synthetase type; [17]), both of which seem unlikely candidates for interacting with SCO5746 or
SCO1222. However, it is possible that these genes contribute to a dispersed biosynthetic pathway, not involving a
dense genomic clustering. Of course, they could also be
contributing to any other stationary phase process.
Interestingly, we see a strong neighborhood conservation of most of the candidate orphan genes in other Streptomyces species (Figure 2). In some cases, the annotation
of the neighbors does suggest at least a broad functional

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Figure 1 Average expression profile of the top 25 candidate orphan genes. This figure shows the expression profiles of the candidate
genes during the phosphate-starvation experiment described in the text. Phosphate depletion occurs between time point 15 and 16 (i.e.,
between 35 and 36 hours after the start of the culture).

category: for example, SCO1521/1522 might be involved
in DNA remodeling during recombination, as their conserved neighbors are a Holliday junction resolvase and
DNA helicase (RuvABC complex); and SCO2081 might
play a role in cell division, matching its conserved

neighbor, the cell division protein ftsZ [18]. However,
most of the conserved neighbors are hypothetical proteins
themselves and do not seem to immediately identify a
putative function for most of the orphan genes; nonetheless, the neighborhood information will be valuable for the

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Figure 2 Neighborhood conservation of the top 20 candidate orphan genes. This figure shows annotation conservation of the neighbors
of orphan genes in four sequenced Streptomyces genomes. The conserved orphan gene is shown in the centre, and the two neighbors on each
side are shown in the form of arrows. Each arrow has four sections, corresponding to the four Streptomyces species: S. coelicolor, S. avermitilis, S.
griseus and S. scabies. They are colored in blue where the annotation matches that of S. coelicolor. The annotation of the S. coelicolor homolog is
listed above each gene if it is conserved in at least one of the other species; if at least two of the other species share another annotation, this is
listed in brackets.

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design and interpretation of the most efficient experimental perturbations. The dynamic expression pattern of each
of the neighborhoods depicted in Figure 2 is shown in
Additional File 2: SupplementaryFile1.pdf. This illustrates,
e.g., that the expression of SCO1522 shows a very similar
expression trend compared with its left and right neighbors (SCO1521 and SCO1523), confirming the relevance
of adjacency on the genome for predicting gene
functionality.
The prioritization reported in this paper of course
depends on implicit assumptions about what constitutes
a protein of interest. Here we were a priori interested in
any protein that is maintained by purifying selection in
a large number of genomes, indicating that it is involved
in a generally important physiological process. On the
other hand, we assumed that genes that show strong
gene expression responses to a major physiological perturbation are more likely to be functionally relevant
under the conditions studied. Genes that are not
expressed or not finely controlled are more likely to
have more specialized functions. This approach does not
exclude the identification of housekeeping genes, which
may not be directly involved in the physiological process
studied in the gene expression analysis, as these genes
still tend to show dynamic expression patterns (as evidenced, e.g., by the ribosomal protein genes [1]). The
results are, however, affected by the availability of gene
expression data sets and will become more informative
once other large-scale expression studies, comparable to
the one used here, become available.

Conclusions
Our aim was to prioritize protein coding orphan genes
(hypothetical proteins with unknown function) for
further experimental characterization of their function.
We developed an algorithm to detect dynamic switches
in a large gene expression time course data set, and
assigned an “expression dynamics” score to every orphan
gene, arguing that genes that show substantial expression changes corresponding to biologically relevant
events would be most interesting to follow up. We also
summarized the available evolutionary information in a
“conservation” score across a broad range of organisms
(many actinomycetes, other bacteria and various nonbacterial species). We combined the “expression
dynamics” rank and “conservation” rank to identify a
robust list of 30 high priority orphan genes, which are
promising candidates for detailed experimental study.
Methods
Genome sequence analysis

For the phylogenomic profiling, we studied the complete
genome sequences of the 44 actinomycete species,
which were also used in our earlier phylogenetic study

Page 6 of 8

[3]: Arthrobacter aurescens TC1, Acidothermus cellulolyticus 11B, Bifidobacterium adolescentis ATCC 15703,
Bifidobacterium longum NCC2705, Corynebacterium
diphtheriae NCTC 13129, Corynebacterium efficiens YS314, Corynebacterium glutamicum ATCC 13032, Corynebacterium jeikeium K411, Clavibacter michiganensis
subsp michiganensis NCPPB 382, Frankia alni ACN14a,
Frankia sp CcI3, Frankia sp EAN1pec, Kineococcus
radiotolerans SRS30216, Leifsonia xyli subsp xyli str
CTCB07, Mycobacterium avium subsp, paratuberculosis
str k10, Mycobacterium avium 104, Mycobacterium
bovis BCG Pasteur 1173P2, Mycobacterium bovis subsp
bovis AF2122 97, Mycobacterium gilvum PYR-GCK,
Mycobacterium sp JLS, Mycobacterium sp KMS, Mycobacterium leprae TN, Mycobacterium sp MCS, Mycobacterium tuberculosis H37Ra, Mycobacterium
smegmatis str MC2155, Mycobacterium tuberculosis
CDC1551, Mycobacterium tuberculosis F11, Mycobacterium tuberculosis H37Rv, Mycobacterium ulcerans
Agy99, Mycobacterium vanbaalenii PYR-1, Nocardioides
sp JS614, Nocardia farcinica IFM 10152, Propionibacterium acnes KPA171202, Rhodococcus sp RHA1, Renibacterium salmoninarum ATCC 33209, Salinispora
arenicola CNS 205, Streptomyces avermitilis MA 4680,
Saccharopolyspora erythraea NRRL 2338, Streptomyces
griseus strain IFO13350, Streptomyces scabies strain
8722, Salinispora tropica CNB 440, Thermobifida fusca
YX, Tropheryma whipplei str Twist, Tropheryma whipplei TW08 27. This was complemented by the genomes
of 6 eukaryotes (Caenorhabditis elegans, Arabidopsis
thaliana, Homo sapiens, Plasmodium falciparum 3D7,
Drosophila melanogaster, Saccharomyces cerevisiae), 2
archaea (Haloterrigena turkmenica, Methanosarcina
acetivorans), and 5 other model bacteria from different
taxonomical classes (Bacillus subtilis, Escherichia coli
K12, Lactobacillus plantarum WCFS1, Staphylococcus
aureus, Streptococcus pneumonia AP200). Putative
homologs were identified as reciprocal best BLAST hits.
The conservation score was calculated in three steps: (1)
the genes were independently ranked according to the
number of species of actinomycetes, other bacteria, and
non-bacteria in which they have a putative homolog; (2)
their ranks in the bacteria and non-bacteria lists were
averaged; and (3) the resulting rank and the rank in the
actinomycete list were averaged again to produce the
final rank.
Gene expression data

Details about the gene expression dataset and experimental conditions can be found in [1,2]. Briefly, mRNA
abundance was assessed at 32 time points during a 68hour phosphate-limited fermentor culture of S. coelicolor, using custom-designed Affymetrix genechips; the
data reveal a complex sequence of gene expression

Alam et al. BMC Research Notes 2011, 4:325
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switches, affecting a large diversity of biological processes, from phosphate uptake to secondary metabolism
and protein biosynthesis.
Dynamic expression detection

To identify genes that show a dynamic expression along
the time course, and in particular genes that have a
clear expression switch at one time point, we used the
following iterative algorithm (in pseudo code):
Input: a vector v of gene expression data
Output: minPvalue, the p-value of the switch-like
dynamic expression
Initialize: minPvalue: = 1
For each value i in the set (2 to (length(v) - 2)), do
j:=i+1
MaxWindowSize < - min(i, length (v) - i)
For each position p in the set ((i - MaxWindowSize + 1) to i - 1), do
q : = j + (i - p)
Pvalue: = p-value of the t-test comparing v[p:
i] and v[j:q]
If (Pvalue < minPvalue), then
minPvalue: = Pvalue
end
end
end
return minPvalue
An R implementation of the algorithm is available
from the authors upon request.

Additional material
Additional file 1: Table of generally conserved actinomycete orphan
proteins. The table lists 381 Streptomyces coelicolor orphan genes that
are generally conserved in other actinomycetes genomes (more than
half of the 44 actinomycete species examined; blue gene numbers). Of
these, the top 73 are present in at least three of five representative nonactinomycete bacterial genomes (red; 25 are present in all five of these
species). The top 22 genes also have putative homologues (reciprocal
best BLAST hits) in at least half of the species in a representative set of
eight non-bacterial genomes (green).
Additional file 2: Gene expression profile of gene neighborhoods.
Expression profile of the genes shown in Figure 2.

Acknowledgements
MTA was funded by a GBB scholarship, University of Groningen. ET was
funded by a Rosalind Franklin Fellowship from the University of Groningen.
RB is supported by an NWO-Vidi fellowship.
Author details
Institute of Molecular, Cell and Systems Biology College of Medical,
Veterinary and Life Sciences, Joseph Black Building B3.10, University of
Glasgow, G12 8QQ, Glasgow, UK. 2Groningen Bioinformatics Centre,
Groningen Biomolecular Sciences and Biotechnology Institute, University of
Groningen, The Netherlands. 3Department of Microbial Physiology,
1

Page 7 of 8

Groningen Biomolecular Sciences and Biotechnology Institute, University of
Groningen, The Netherlands.
Authors’ contributions
ET and RB designed the study. MTA performed the analysis. RB and MTA
wrote the manuscript. All authors revised the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Received: 30 May 2011 Accepted: 7 September 2011
Published: 7 September 2011
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Cite this article as: Alam et al.: Prioritizing orphan proteins for further
study using phylogenomics and gene expression profiles in
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