The Importance of Bioinformatics Tools in Medical Field: From

Prediction to Prescription

Syarif Hidayat, Khariri, Setyo Adiningsih, Rina Isnawati, Nona Rahmaida Puetri, Putri Reno Intan,

Uly Alﬁ Nikmah, Sunarno and Novaria Sari Dewi Panjaitan

Center for Biomedical Research, Research Organization for Health, National Research and Innovation Agency (BRIN),

Cibinong Science Center, Bogor Km. 46, West Java, Indonesia

Keywords:

Bioinformatic, Bioinformatic Tools, Prediction, Antibiotic Resistance, AMR.

Abstract:

The bioinformatics study was a modernly designed study that enabled scientists worldwide, especially those

working in genetic in living organisms, to do deeper analysis in researches. In recent reported studies regarding

the bioinformatics tools used in the analysis, the issues regarding how to utilize well-developed bioinformatics

tools in the studies requiring wet laboratories works were much discussed. Even though, those tools were being

utilized in the preliminary step as a prediction, the accurate prediction predicted by the bioinformatics analysis

was often guiding the research itself to a more directing research pathway. The growing issues and efforts of

‘personalized medicine’ was a good example of how important bioinformatics tools used in it for physicians

in order to decide the exactly needed prescription subjectively. In this article, a brief descriptive review of the

uses of several bioinformatics tools in the antibiotic resistance in bacterial infection cases. By an advanced

search in PubMed, 78.563 articles regarding bioinformatics and antibacterial resistance were found without

any limitations set on the publication date. However, due to the aim of this article was to brieﬂy overview the

importance of bioinformatics study in helping physicians making the right prescription, especially regarding

the antibiotic use and antibiotic resistance based on recent reports, the limitations was set for only from 2018

to February 2023. Based on the ﬁlter set in MesH and title/abstract terms and publication date, a total of

45.435 articles in this search were found. However, from those 45.435 articles, there were approximately

181 systematic review articles found. These searches showed the needs in scientiﬁc communications between

researcher using the bioinformatics tools and physicians for deciding the most appropriate way to well utilize

the available tools to make better prescription worldwide, as one of many efforts in optimizing the antibacterial

agent uses and against the antibacterial resistances.

1 ANTIBIOTIC RESISTANCES

AND ITS SERIOUSNESS

Antibiotic resistance occurs when bacteria change

over time and become unresponsive to drugs, mak-

ing the undergoing occurred infections more difﬁcult

to treat, spreading disease, and causing severe dis-

ease which highly possibly increase the risk of ill-

ness and death of the patients. Antibiotic resistance

demonstrated as the worldwide problem by World

Health Organization (WHO) was a health problem

which requires real action to combat. In their Fact

Sheet, WHO had explained why this matter has be-

come a global health burden and mentioned that the

antibiotic-resistant pathogenic bacteria had acquired

novel resistance mechanisms which should be unrav-

eled in the studies studied globally.1 In addition, due

to One Health policy, WHO also considered the im-

portance of a coordinated action which could be func-

tion as an approach in combating the antibiotic resis-

tance.

Certain programs were designed by WHO and

widely performed in many countries worldwide, such

as Global Action Plan on Antimicrobial Resistance

(GAP) since 2015, Tripartite joint Secretariat on An-

timicrobial Resistance declared in United Nations

committee meetings in 2016, World Antimicrobial

Awareness Week (WAAW) held annually since 2015,

the Global Antimicrobial Resistance and Use Surveil-

lance System (GLASS) launched also in 2015 in pur-

pose to fulﬁll the knowledge gaps and to inform pos-

sibly and thoughtful strategies, Global Research and

Development priority setting on Antimicrobial Resis-

tance started in 2017, and lastly the Global Antibiotic

166

Hidayat, S., Khariri, ., Adiningsih, S., Isnawati, R., Puetri, N., Intan, P., Nikmah, U., Sunarno, . and Panjaitan, N.

The Importance of Bioinformatics Tools in Medical Field: From Prediction to Prescription.

DOI: 10.5220/0012445900003848

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 3rd International Conference on Advanced Information Scientiﬁc Development (ICAISD 2023), pages 166-171

ISBN: 978-989-758-678-1

Research and Development Partnership (GARDP)

(Organization, 2021).

In several narrative and descriptive review arti-

cles reported recently, several priorities due to the

resistance towards antibiotic was well written and

discussed. Most of the antibiotic resistant-bacterial

isolates were those commonly causing the blood-

stream infections, Acinetobacter baumanii (BaiB and

HuangW, 2022). A. baumannii is an emerging bacte-

rial pathogen that provokes certain types of infectious

diseases in hospitals occurred and reported around

the world. By utilizing the available bioinformat-

ics tools, such as GenVision a component of DNAS-

TAR’s Lasergene Core Suite, the genome of A. bau-

manii isolates which consists of chromosomes and

plasmids were studied.3 A. baumanii isolates often

carry plasmids vary in size and are widespread. Many

of them are associated with the acquisition of an-

tibiotic resistance genes, which could be the reasons

for their ability to well survive in the patients under

treatment with commonly used antibiotics (Salgado-

camargo et al., 2020).

The resistance cases found in patients diagnosed

with tuberculosis (TB) is one of resistance issue that

should not be neglected. Mycobacterium tuberculo-

sis, the causative infectious agent of TB, is one of

the world’s leading killers, but there are a signiﬁcant

number of antibiotics directed against tuberculosis.

This is primarily due to drug resistance mechanisms

present in bacteria leading to multidrug-resistant tu-

berculosis (MDR-TB) (BiswasSS and BorahVV, ). A

variety of computational tools are available that are

used for virtual screening of large numbers of certain

compounds, either synthetic or the plant extracts, in

order to combat the occurring resistance in this bac-

terium. However, till nowadays, there is still no re-

port reported highly successful approach for handling

this matter while the number of resistance case was

reported to continuously increase (YuwonoA et al., ).

Take the antibiotic resistance of Klebsiella pneu-

moniae, a common cause of health-care associated in-

fections known as nosocomial infections, as another

example. K. pneumoniae is one of bioﬁlm-well form-

ing bacteria (LiY and ZhangL, 2022). The ability

of this bacterium in forming the bioﬁlms could be

the reason of largely resistance found in isolated K.

pneumoniae isolates. The ability to form bioﬁlms has

been shown to be highly resistant to antibiotics (LiY

and ZhangL, 2022; Panjaitan, 2019). Especially in K.

pneumoniae, the genetic information difference and

the different expression levels of certain genes in this

bacterium was reported to play an important role in

regulating its ability to form the bioﬁlm, which surely

affects its resistance towards certain antibiotic. Et-

cABC, the novel clustered genes in an operon, was

previously reported and proposed to be the genes

regulating the bioﬁlms formation in K. pneumoniae

STU-1 (Panjaitan, 2019). However, etcABC is not the

only genes regulating virulence factors of K. pneu-

moniae. The components of phosphoenol-pyruvate

phosphotransferase system (PTS) in K. pneumoniae

was reported also to affect the formation of bacterial

bioﬁlms (HorngYT et al., 2018).

Many approaches had been developed and pro-

cessed by WHO worldwide. However, till nowadays,

the approach that could be utilized as a way out still

stays being a question. What approach could it be?

Although predictions are reasonably accurate, medi-

cal interventions to improve patient outcomes are of-

ten too late to be effective. To advance medical care

of our patients, this study aims to identify micro-

bial characteristics associated with poor clinical out-

comes.

2 BIONFORMATICS TOOLS

USED FOR PREDICTING AND

ADDRESSING THE

ANTIBIOTIC RESISTANCES

In recent years, the amount of molecular informa-

tion attributed to clinical data has increased signif-

icantly, thanks to the implementation of approaches

and resources that enable an ’omics’ view of dis-

eases. Bioinformatics is therefore seen as essential

for managing vast amounts of data for better diagno-

sis and treatment of rare and complex diseases. In-

deed, bioinformatics approaches are capable of ﬁnd-

ing relationships between genomics, transcriptomics,

proteomics, metabolomics, interactomics, and other

’omics’ data that can elucidate complex interactions

between different levels and timescales. The tech-

niques of data mining enable the simulation of com-

plex systems and the construction of dynamic net-

works with the aim of developing predictive, preven-

tive and personalized medicine.

In order to further explore the molecular and ge-

nomic characteristics of bacterial isolates with resis-

tance towards antibacterial agents, whole-genome se-

quencing and analysis was widely utilized nowadays.

The use of next generation sequencing (NGS), a se-

quencing platform, started to be very useful for AMR

analysis (SabatAJ and AkkerboomV, 3 01). Next-

generation DNA sequencing machines are generat-

ing sequence data at unprecedented speeds, but tra-

ditional single-processor sequence alignment algo-

rithms struggle to keep up.

The Importance of Bioinformatics Tools in Medical Field: From Prediction to Prescription

167

Two sequencing platforms, Ion Torrent and Illu-

mina, were compared previously by using MiSeq and

Bioinformatics for Analysis of AMR Genes data anal-

ysis pipeline after considering all differences between

two platforms.10 However, the results of that partic-

ular study suggested that whether the platform (Ion

Torrent or Illumina) or sequencing chemistry used has

little impact on the outcome of the AMR data (SoniT

et al., 2022). For any certain region of genetic in-

formation or protein sequences which could not be

found by annotation or BLAST searches; an exper-

imental approach is needed to identify such replica-

tion regions. The advance method and strategy of

next-generation sequencing has enabled researchers

to analyze whole genomes or multiple genes simul-

taneously for mutation detection or gene expression

studies (Mohini et al., 2023). A table regarding the

well-developed and useful bioinformatics tools for

the genomic based data analysis was provided in Ta-

ble 1. Till nowadays, there are several bioinformat-

ics tools which had been developed and being uti-

lized in studies worldwide, such as AzureBlast, Blas-

tReduce, CloudBLAST, CloudAligner, CloudBurst,

Crossbow, DistMap, Eoulsan, FX, GATK, Hadoop-

BAM, HadooZiper, Seal, SeqWare, and TIARA (Ta-

ble 1). These tools were created for different purposes

in metagenomics study. However, those tools are con-

sidered and reported useful.

Table 1: Bioinformatic tools for genomic based data analy-

sis (Mohini et al., 2023).

No.Available

bioinfor-

matics

tools

Deﬁnitions Description and

functions in previ-

ous study

Ref.

1. AzureBlast A case study of develop-

ing science applications

on the cloud

Parallel BLAST

running on the

Microsoft Azure

cloud computing

platform

(LuW,

2010)

2. BlastReduce New parallel read map-

ping algorithms opti-

mized for matching se-

quence data from these

machines to reference

genomes

BLAST-based on

Hadoop

(SchatzMC,

2009a;

KhawlaT

and

Azed-

dineZ,

2018)

3. CloudBLASTCombination of MapRe-

duce and Virtualiza-

tion on Distributed

Resources for Bioinfor-

matics Applications

Cloud-based

BLAST imple-

mentation

(Calabre-

seB,

2021)

4. CloudAligner fast and full-featured

MapReduce based tool

for sequence mapping

method

Genomic sequence

mapping (se-

quence mapping

technology based

on MapReduce

that is full- fea-

tured and rapid)

(NguyenT

and

RudenD,

2011)

5. CloudBurst A highly sensitive

read mapping with

MapReduce, a new

parallel read map-

ping algorithms

optimized for map-

ping next-generation

sequence data to

the human genome

and other reference

genomes for use in a

variety of biological

analyses, including

SNP discovery,

genotyping, and

personal genomics

MapReduce-based

genomic sequence

mapping using

very sensitive

short reads

(SchatzMC,

2009b)

6. Crossbow Analysis of genomic

sequences utilizing

cloud computing,

including read

mapping and SNP

calling

Genotyping, SNP

detection, Read

mapping, Service

composition

(Crossbow,

)

7. DistMap A Toolkit for Dis-

tributed Short Read

Mapping on a

Hadoop Cluster

An integrated

workﬂow for short

read mapping

against a user-

speciﬁed reference

genome.

(PandeyRV,

2013)

8. Eoulsan A Cloud Computing-

Based Framework

Facilitating High

Throughput Se-

quencing Analyses

RNA sequencing

analysis based on

a scalable, ﬂexible

framework built

on the Hadoop

platform

(JourdrenL

et al., 4

10)

9. FX An RNA-Seq analy-

sis tool that runs in

parallel on a cloud

computing infras-

tructure to estimate

gene expression lev-

els and call genomic

variants.

Purposed for

RNA-seq data

analysis

(HongD

and soo,

2012)

10. GATK The industry stan-

dard for identifying

SNPs and indels in

germline DNA and

RNAseq data. Its

scope now includes

somatic short vari-

ant calls and is being

extended to address

copy number (CNV)

and structural varia-

tion (SV)

Next-generation

resequencing data

management for

sequence ﬁles,

a gene analysis

toolset

(BathkeJ,

)

11. HadoopBAM The integration be-

tween analytic soft-

ware and BAMﬁles

Management of

sequence ﬁles,

Directly ma-

nipulating next

generation se-

quencing data in

the cloud

(NiemenmaaM

et al.,

2012)

12. HadooZiper A cloud envi-

ronment for bio-

informatics data

analysis

(BretaudeauA

and

CollinO,

2012)

13. Seal A distributed short

read mapping and

duplicate removal

tool

Genomic sequence

mapping (using

Hadoop’s

(PiredduL

and

Zanet-

tiG,

2011)

No. Available

bioinfor-

matics

tools

Deﬁnitions Description and

functions in

previous study

Ref.

duplication re-

moval and short

read pair mapping)

14. SeqWare The query engine

enabling information

from databases,

storing and searching

sequence data in the

cloud

Management of

sequence ﬁles

(ConnorBDO

and Nel-

sonSF,

2010)

15. TIARA A database for ac-

curate analysis of

multiple personal

genomes based on

cross-technology

A user-friendly

genome browser,

which retrieves

read-depths (RDs)

and log2 ratios

from NGS and

CGH arrays

(HongD

and

JuYS,

2011)

ICAISD 2023 - International Conference on Advanced Information Scientiﬁc Development

168

3 THE POSSIBILITY OF

BIOINFORMATICS TOOLS

BEING USED BY PHYSICIANS

The remaining question is that could the available

bioinformatics tools and bioinformatics based anal-

ysis be really manifested and utilized by working

physicians in helping them making the better deci-

sions in prescribing the needed medications, partic-

ularly antibacterial agents? There are a lot of con-

sideration and thoughts made by a physician while

handling a patient, especially one diagnosed with in-

fectious diseases. A scheme describing a pathway as

an example of how useful bioinformatics tools could

be utilized in deciding a prescription, particularly re-

garding the antibiotic resistance in bacterial infectious

diseases, was provided in Figure 1.

Figure 1: Scheme describing the simple useful example of

how bioinformatic analysis was utilized in making a deci-

sion for antibiotic prescription (ConnorBDO and NelsonSF,

2010).

A previous behavior study had reported their re-

sults regarding the acceptance of bioinformatics ap-

plications by biomedical researchers, the decision-

making processes underlying the selection of tools

for primer design and microarray analysis, and the

long-term impact of training on these behaviors.28

The results of that particular study suggested a num-

ber of possible roles for medical libraries in support-

ing bioinformatics implementations, including infras-

tructure support, consulting, and training. Addition-

ally, libraries can provide services and initiate col-

laborative research on complex tasks.28 Further in-

vestigation of how bioinformatics can be integrated

into biomedical research and to develop training mod-

ules for improved bioinformatics uptake was also pro-

posed (ShachakA and FineS, 2007).

Bioinformatics, ”the science of managing and an-

alyzing biological data using advanced computational

techniques”, is indeed a useful tool since it could

reveal the unknown genetic materials in infectious

agents. However, a useful tool could not be consid-

ered useful unless most of people know how to use it

regardless of the ﬁeld. Therefore, the question raised

here is how to improve the use of bioinformatics tools

by physicians whom probably are not involved in re-

searches?

4 PIPELINE OF HOW

BIOINFORMATICS TOOLS

ARE BEING USED IN MEDICAL

EFFORTS AND ACTIVITIES

The bioinformatics analysis pipelines were usually

consisting continuously dependent processes which

consist of nucleic acid material (DNA/RNA) isolation

from the clinically or environmental isolated bacterial

isolates, assemble sequence data (directly from en-

vironmental samples) to build contiguous sequences

(contigs and scaffolds), prediction of genes (and puta-

tive proteins) based on the assembled data, prediction

of putative proteins predicting domains, functions and

pathways. These pipelines were widely utilized in

metagenomics analysis (RoumpekaDD et al., 2017).

Figure 2: Scheme of a typical bioinformatics tools used in

genomic study. Genomic material (taken directly from en-

vironmental samples) is sequenced and processed using as-

sembly, gene prediction, and gene annotation tools. Finally,

the results are shared among scientiﬁc groups around the

world. (RoumpekaDD et al., 2017).

The annotated sequences and identiﬁed genomic

information such as genes and regulatory elements

are the next steps of metagenomic analysis pipeline.

The short reads generated by NGS (sequencing pro-

cess) are usually hard to be assembled. Even suc-

cessfully being assembled, the resulted contigs are of-

ten too short and fragmented to be analyzed. High-

throughput platforms may require more samples to be

sequenced in parallel to

The Importance of Bioinformatics Tools in Medical Field: From Prediction to Prescription

169

provide an economic advantage over smaller se-

quencing platforms. One of ﬁnal goals of these conti-

nous pipelines is to generate and develop the diagnos-

tic kits for certain infectious agents which could be

detected through a simple detection method due to the

genomic information available.30 Therefore, the fu-

ture studies in bionfomatics are continuously needed

to be improved, for its actual use in medical ﬁeld.

The ﬁnal step of these pipelines is sharing the

metagenomic sequences or data. Data sharing under-

pins reproducible science, but expectations and best

practices are often vague. The funder, researcher,

and publisher communities continue to wrestle with

what should be requested or encouraged. We focus on

stakeholders in the scientiﬁc community to shed light

on the reasons for data sharing, technical challenges,

and social and cultural challenges. In biomedical re-

search, participants are important to these stakehold-

ers. Ethical sharing must consider both the value of

the research effort and her cost of participant privacy.

The current best practices for different types of ge-

nomic data and how coordinating incentives fosters

ethical data sharing that accelerates science has been

discussed elsewhere(ByrdJB et al., 2020).

5 DATABASE SEARCH

STRATEGY

The articles related to bioinformatics tools used

in studies regarding antibacterial resistances were

searched in PubMed through an advanced search by

(((antibacterial drug resistance [MeSH Terms]) OR

(antibacterial drug resistance [Title/Abstract])) AND

(bioinformatics [MeSH Terms]) OR (bioinformatics

[Title/Abstract]). From this search, 78.563 articles

were found. In addition, the date publication was set

for 2018 to 2023 which was followed by a ﬁlter for

systematic review. Respectively, 45.435 articles and

181 articles were found for each search (Filters: Sys-

tematic Review, in the last 5 years. Sort by: Most

Recent). Manually, the latest issues of relevant publi-

cations and a reference list of included text and related

articles were screened.

6 CONCLUSIONS

Effective use of bioinformatics in biomedical research

has important implications for discovering the under-

lying mechanisms and potential treatments for nu-

merous diseases. Bioinformatics knowledge and de-

velopment of bioinformatics based tools has made a

possible way to access the unknown genes regulating

the bacterial phenotypes, such as antibacterial agents

resistances, genetic information, novel proteins and

many other features of a sample at a genome-wide

level, which presents considerable opportunities for

secondary analysis and its utilization in biomedical

researches and medical ﬁeld. In this article, several

useful bioinformatics tools were listed and brieﬂy dis-

cussed. The difﬁculties of manifestation of bioinfor-

matics tools use in medical or health ﬁeld were also

openly discussed. The importance of bioinformatics

tools in biomedical research had been realized in im-

proving the target of research, especially in antibac-

terial resistance issue, even to personalized medicine.

Therefore, the improved –user friendly bioinformat-

ics tools development is highly recommended for be-

ing further studied.

ACKNOWLEDGEMENTS

All authors would like to acknowledge to National

Research and Innovation Agency (BRIN) for the

given support for the researchers and to convey grat-

itude to all researchers in the Center of Biomedical

Research for the hard working and efforts in biomed-

ical researches.

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