The Biologist (Lima), 2017, 15(1), jan-jun: 15-22

ORIGINAL ARTICLE / ARTÍCULO ORIGINAL

NEW PHYLOGENETIC ANALYSIS METHOD USING TAXPLOT,

AND ITS APPLICATION ON ACUTE DIARRHEAL DISEASE-CAUSING BACTERIA

NUEVO MÉTODO DE ANÁLISIS FILOGENÉTICO USANDO TAXPLOT,

Y SU APLICACIÓN EN BACTERIAS CAUSANTES DE ENFERMEDAD DIARREICA AGUDA

1Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Av. Honorio Delgado 430, Lima 31,

Lima, Perú. Hospital Nacional Docente Madre Niño San Bartolomé, Av. Alfonso Ugarte 825, Lima 01, Lima, Perú.

3Universidad Nacional Federico Villarreal, Facultad de Ciencias Naturales y Matemáticas. Jr. Río Chepén 290,

Lima 10, Perú

*E-mail: jeel.moya.s@upch.pe / roberto.ubidia.i@upch.pe

1,3 1,2,*

Roberto Adolfo Ubidia-Incio & Jeel Jr. Moya-Salazar

ABSTRACT

Keywords: database – genome-wide analysis – phylogenetics – protein

Proteins are important in phylogenetics because they show conservation, not only in their sequence, but also in their

functions and the properties of their different substructures due to residue or amino acid family conservation. The

analysis of the set of data from a great number of proteins will show us properties that have been the driving force of

species diversification. Here, we present a phylogenetic method for constructing cladograms using TaxPlot data. We

constructed a cladogram using the UPGMA method using the total hits obtained from all the combinations of TaxPlot

previously transformed into percentages of similarity. This cladogram based on the similarity of bacterial proteomes

presents a large similarity with the relations that exist for the analyzed organisms based on conserved sequences.

ISSN Versión Impresa 1816-0719

ISSN Versión en linea 1994-9073 ISSN Versión CD ROM 1994-9081

RESUMEN

Palabras clave: análisis genómico – base de datos – filogenética – proteína

Las proteínas son importantes en la filogenética dado que muestran la conservación, no solo de sus secuencias, sino

también de sus funciones y de las propiedades de sus diferentes subestructuras debido a la conservación de las

familias de aminoácidos. El análisis de grupos de datos de un gran número de proteínas puede mostrar sus

propiedades que han tenido fuerza de manejo de la diversificación de especies. Aquí, presentamos un nuevo método

filogenético para la construcción de cladogramas usando la base de datos TaxPlot. Hemos construido un cladograma

utilizando el método UPGMA de acuerdo con los aciertos (Hits) totales obtenidos a partir de todas las combinaciones

de TaxPlot previamente transformados en porcentajes de similitud. Este cladograma basado en la similitud de los

proteomas bacterianos presenta una gran similitud con las relaciones que existen para los organismos analizados en

base a secuencias conservadas.

The Biologist

(Lima)

The Biologist (Lima)

Genome analysis is a useful tool because it allows

us to understand diverse biologic phenomena by

showing the conservation of the genes responsible

of specific functions, not only one isolate gene but a

group of them with a function that has been

conserved during the course of evolution (Roman

et al., 2000). Comparing genomes of many related

organisms allows also seeing and understanding

how the emergence of new genes can help to

develop new functions inside a pre-established

gene system. That is why identifying orthologs is

critical to predict protein functions on new strains

or species that cause a determined pathology

(Roman et al., 2000; Tatusov et al., 2003). Without

doubt, the later would benefit the understanding of

the pathogenic mechanisms employed by many

organisms such as Acute Diarrhea Disease causing

bacteria, the way the appeared and diversified.

Moreover, in a greater measure, the utility when

looking for strategies against them and preventing

their infection (Tatusov et al., 2003).

Comparative genomics offers a useful scope for

understanding information at a genomic level, for

this, the first objective when a genome is

sequenced, is to identify the functional regions,

both genes and regulatory sequences. A part of that

information needs experimental work, but another

part could be obtained from comparative analysis

in silico, which can facilitate the identification of

those elements (Tatusov et al., 2003). Thus, the

purpose of comparative genomics is, through the

comparison of genomes of different species, to

understand how those species have evolved, and

the functions of their genes and non-coding regions

(Thorat & Thakare, 2013).

The bioinformatics tool, TaxPlot, that belongs to

NCBI (National Center for Biotechnology

Information), allows us to observe the similitude

among three organisms based on the proteome of

one of them, it refers to the amount of similar

proteins from the genomes of three different

species, using the first one as a query, from which

every protein sequence is taken and compared with

p r e - c o m p u t e d B L A S T r e s u l t s

(http://blast.ncbi.nlm.nih.gov/Blast.cgi) of the

other two species (Wheeler et al., 2001). This type

of analysis has been previously used to study

The Biologist (Lima). Vol. 15, Nº1, jan - jun 2017

INTRODUCTION similarities between other organisms, such as

archaeas (Makarova et al., 2015). In other cases,

these tools have been used to predict genes form

recently sequenced genosomes, for example on

Serratia plymuthica AS-12 (Roman et al., 2000,

Neupane et al., 2012), Staphylococccus

epidermidis (Thorat & Thakare, 2013), and others

(Heidelberg et al., 2000, Bhagwat & Bhagwat,

2008; Siddaramappa, 2007). This tool allows us to

analyze genomes where a comparison has been

previously done, so it is not needed to download

complete genomes in order to do an analysis.

Nevertheless, it has the disadvantage of not being

continually maintained, so the number of available

genomes is limited and not updated.

Acute Diarrhea Disease is one of the four principal

causes of child mortality in the world and one of

three that has been related to climate change

(Murga et al., 1993; MINSA, 2015). In the

Americas, it has been estimated that 112 000

annual deaths are caused by diarrheal diseases

(WHO, 1999). This affection causes alterations on

the human development in three fundamental

aspects: limiting the organic growth, reducing the

intellectual capital, and increasing the Disability-

Adjusted Life Years (DALY), mainly in children

under 2 years.

The principal causes of Acute Diarrhea Disease are

the bacteria from the genus Campylobacter,

Salmonella, Shigella, Vibrio, Proteus and

Enterococcus faecalis; and also Escherichia coli

O157:H7, Klebsiella pneumoniae, Morganella

morgani, Aeromonas oxytona, among others

(Cama et al., 1999; WHO, 1999; Seas et al., 2000;

Winn et al., 2006).

The objective of the present investigation was to

design a novel phylogenetic method using the data

from Diarrhea causing disease-bacteria listed in the

TaxPlot tool, and to analyze their genomes and

establish a proteomic-scale relationship between

them.

The application of this method was done through

an analytic, retrospective, cross-sectional study

MATERIALS AND METHODS

Ubidia-Incio & Moya-Salazar

applied to acute diarrhea disease-causing bacterias.

Species: The species considered for testing this

method: Campylobacter jejuni subsp jejuni

(NCTC 11168=ATCC700819) [Cje], Shigella

dysenteriae (strain Sd197) [Sdy], Salmonella

entérica subsp enterica (serovar Typhimurium

strain LT2) [Sen], Vibrio cholerae (01biovar El Tor

strain N16961) [Vch], E. coli O157:H7 (strain

Sakai) [Eco], Proteus mirabilis (strain H14320)

[Pmi], E. faecalis (strain V583) [Efa], K.

pneumoniae (strain 342) [Kpn] (Winn et al.,

2006; Cama et al., 1999).

Resources for genome analysis: An inter-protein

comparative analysis of each species was done

w i t h t h e t o o l Ta x P l o t f o r m N C B I

(http://www.ncbi.nlm.nih.gov/sutils/taxik2.cgi?is

bact=1) with the objective of observing the degree

of similitude between orthologs proteins of the

analyzed species. The relation between each

species (“query” species) and the others in groups

of two (comparative species) was observed.

Techniques for collecting and processing data:

The number of total hits was used; this means, the

number of proteins that produced hits for the two

comparative species based on the total number of

proteins of the query species without taking into

account the bias in the similitude towards any of the

comparative species. All this initial data was

tabulated in a comparative matrix with the

variables [Cje], [Sdy], [Sen], [Vch], [Eco], [Pmi],

[Efa] and [Kpn], where the relationship between

the degrees of similitude was analyzed.

Eight organisms were included; we used TaxPlot as

a tool to observe the similitude between the

selected bacteria based on their proteome instead of

the classical reach in which conserved regions are

evaluated. The plots generated by this tool, provide

us with total hits data, that are hits obtained from

comparing all the proteins from a query organism

against the protein from other two species selected,

through pre-calculated BLAST scores, those hits

were distributed depending on the degree of

similarity to one or the other species.

Taxonomy: A phylogenetic classification of the

proteins codified in the complete genomes was

done through the creation of cladograms, using the

UPGMA method (unweighted paired group means

analysis) (Kuske et al., 2002), using the data from

The Biologist (Lima). Vol. 15, Nº1, jan - jun 2017

each query species, joining the two species with a

higher percentage of hits, then calculating the mean

of the values of the two joint species against all the

other, and repeating this process until every species

had been joined (Fig. 1). Finally, a consensus

cladogram was created based on the eight

cladograms previously created.

A cladogram based on rRNA 16S was made using

the software Phylip version 3,696 (University of

W a s h i n g t o n ,

http://evolution.genetics.washington.edu

/phylip.html) and visualized with TreeView

version 1,6.6 (University of Glasgow, http://

taxonomy.zoology.gla.ac.uk/rod/treeview.html) in

order to compare the method based on conserved

sequences alignment and the method presented

here (Fig. 2).

Data Analysis: Data analysis was performed in

four basic processes: Codification, tabulation,

table construction, and preparation of graphics and

cladograms.

Limitations: In principle, the presentation of

analyzed species does not include the totality of

existent enteropathogens because TaxPlot does not

include all of them on its database. Second, there is

no bioinformatics tool available for designing

cladograms with data from TaxPlot. Lastly,

function patterns were not evaluated for

enterobacteria. In spite of these limitations, our

research contributes to the bioinformatics

development applied to clinic microbiology.

New phylogenetic analysis method

With the help of the bioinformatics tool TaxPlot of

NCBI we could access to similitude data of all the

proteome of the Acute Diarrhea Disease-causing

bacteria analyzed in groups of three. We obtained

168 plots where it was possible to observe the

similitude between each species selected as query

towards other two from the group of analyzed

bacteria. From this data, previously transformed

into percentages, obtained from the total hits for

each comparison, a cladogram was created (Fig. 2).

The methodology for elaborating this cladogram is

described in the flowchart presented in Figure 1.

RESULTS

The Biologist (Lima). Vol. 15, Nº1, jan - jun 2017

Ubidia-Incio & Moya-Salazar

Figure 1. Flowchart for the development of the cladogram based on TaxPlot data for the ADD-causing species.

The Biologist (Lima). Vol. 15, Nº1, jan - jun 2017

New phylogenetic analysis method

Figure 2. Comparative cladograms. A. Consensus tree obtained with the UPGMA method with the total hits data obtained with

the bioinformatics tool TaxPlot (numbers indicate the percentage of siilitude). B. Phylogenetic tree where the studied groups

have been highlighted in green frames, showing the evolutionary divergence [modied from Ciccarelli et al. (2006), C.

Cladogram based on rRNA 16S sequences from the analyzed species using the software Phylip and TreeView.

The Biologist (Lima). Vol. 15, Nº1, jan - jun 2017

Ubidia-Incio & Moya-Salazar

The cladogram based in proteome similitude

presents a great similitude with the relation that

exists for these organisms based on conserved

sequences (Fig. 2) (Montiel, 1997; Moran et al.,

2005; Chieh-Hua et al., 2011; Neupane et al.,

2012). When comparing cladograms (TaxPlot,

alignment based on protein universal families, and

rRNA 16S), in general, the analized bacteria form

very similar groups. Campylobacter jejuni showed

a plesiomorphic character.

It is noticeable the separation between

Enterobacteriaceae (S. enterica, E. coli O157:H7,

S. dysenteriae, P. mirabilis and K. pneumoniae)

and Vibrionaceae (V. cholerae). Also, among this

wh ole group ( Gam mapro teo bacte ria ),

Epsilonproteobacteria (C. jejuni) and Firmicutes

(E. faecalis), where the similitude among

enterobacteria ranges between 63,45% and 68,81%

with the method based on TaxPlot, nevertheless,

when incorporating bacteria from other clades this

similitude diminishes drastically, to 56,06% when

incorporating V. cholera, 41.08% for E. faecalis

and 32.14% for C. jejuni.

The only exception to the similitude of results

between the method based on TaxPlot and the

method based on the rRNA 16S sequence is the

relation for S. dysenteriae, S. enterica and E. coli

O157:H7, where we have E. coli and S. enterica

more related among them than with S. dysenteriae.

The usual order is Escherichia coli more related to

S. dysenteriae rather than S. enterica (Fig. 2).

This method seems to have as limitation the

difference in the number of proteins of the query

species. C. jejuni has the lowest number (1623), in

comparison with over 3000 proteins in the other

bacteria, thus the low number of coincidences

makes it appear as the farthest, while methods

based on protein universal families (Chieh-Hua et

al., 2011) shows it is near the other proteobacteria.

Being E. faecalis the farthest as it belongs to the

phylum Firmicutes (Ciccarelli et al., 2006).

Curiously, when aligning and obtaining a

cladogram from the sequences of rRNA 16S, we

obtain the same order between these two bacteria

with respect to the result obtained comparing the

proteome (TaxPlot, Fig. 2).

The method we present here represents a holistic

approximation to the study of phylogenetic

relationships between close species that could be

contrasted against other more specific

approximations in order to observe the

evolutionary behavior in organisms that share a

common environment or niche. In the case of

bacteria, it is known that there have been many

events of horizontal gene transfer (HGT) making it

more complex the identification of the

evolutionary history in these groups as an

orthologous gene may be more similar for two

organisms that are not necessarily the closest,

evolutionarily talking (Akortha & Filgona, 2009;

Stecher et al., 2012). Making a comparison using

the whole proteome this effect can be diminished in

part.

This method reduces the time needed for

phylogenetic analysis due to the help provided by

the existence of tools as TaxPlot that stores

precalculated data, and establishes a phylogenetic

reconstruction at a proteomic level; these features

work well as no distant organisms are chosen that

will diminish the power of this method. These

elements of judgment can be transported as exact

data employing bioinformatics data that could, as

in this case, describe the features of the pathogenic

agents who produce a disease.

The Authors are grateful for the contribution of the

researchers from the Laboratorios de Investigación

y Desarrollo (LID) of Universidad Peruana

Cayetano Heredia for their advice, their time, and

inculcate in us the vocation for bioinformatics.

DISCUSSION

ACKNOWLEDGMENTS

The cladogram based on the similitude of the

proteome of the studied bacteria presents a great

similitude with the relations found or these

organisms using conserved sequences (Fig. 2)

(Moran et al., 2005; Neupane et al., 2012; Moya-

Salazar & Ubidia-Incio, 2015). Additionally, it

shows the relation that exists between our species

based on their proteome, showing as more related

species those that have a higher number of similar

proteins.

The Biologist (Lima). Vol. 15, Nº1, jan - jun 2017

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Accepted January 19, 2017.