Bioinformatics analysis of large-scale genomic data tounderstand microbial diversity and phylogenetic relationshipsof extinct animals.

MORI, Hiroshi Associate Professor

Genome Diversity Laboratory
Department of Informatics

Graduated from the Department of Biology, Faculty of Science, Shinshu University. Completed his master's degree at the Nara Institute of Science and Technology(NAIST). Ph.D. in Science from the Graduate School of Bioscience and Biotechnology, Tokyo Institute of Technology. Assistant Professor, Graduate School of
Bioscience and Biotechnology, Tokyo Institute of Technology, during 2011-2016. Assistant Professor, Laboratory of Genome Evolution, Division of Informatics,
National Institute of Genetics, since 2016. Associate Professor, Laboratory of Genome Diversity, since 2021.

Associate Professor Hiroshi Mori specializes in metagenomic analysis of microbial communities and the analysis ofancient DNA of extinct animals using bioinformatics. He has also developed analytical tools that can easily estimate
the phylogenetic composition of microbes, and a high-speed metagenome sequence similarity search tool. At the rootof his research is his childhood curiosity about the ecology of organisms.

very expensive and laborious. However, bioinformatics, which usescomputers to analyze genomic data, could be studied without highbudgets using genome sequence data in public databases. Thisseemed very interesting to me and ultimately led to my decision toenter the Nara Institute of Science and Technology (NAIST). I had
also considered the National Institute of Genetics (Graduate
University for Advanced Studies) and attended a graduate school
tour, but after much deliberation, I decided to go to Nara. During mymaster's study, I studied with Prof. Ken Kurokawa (who is now also atthe National Institute of Genetics) on the comparative analysis ofbacterial genomes. I also studied metagenomics, the analysis of thegenomes of microbial communities, as the metagenomic sequence
data were just becoming available at that time.

From Animal Behavioral Ecology toBioinformatics
I studied in behavioral ecology as an undergraduate, in part because
I loved catching and observing insects and fish as a child. Becausesnails are slow-moving and cannot fly, their populations are often
isolated by terrain, such as a large river. This can cause speciation,
making them very diverse animals. An important feature of snails isthat most are hermaphrodites. My undergraduate thesis focused on
the differences in reproductive behavior between closely related
species living in the same area. At that time (2000-2003), the resultsof the Human Genome Sequencing Project were just coming out,
which had a huge impact on biology. Perhaps because of this, I was
also interested in genome science, and read genome-related books
and papers in between my undergraduate research.

When Prof. Kurokawa moved to the Tokyo Institute of Technology, I
also entered the Tokyo Institute of Technology as a graduate student.
In my master's study, I analyzed the genome sequence data of certain
bacteria sequenced by using Sanger sequencers. However, around2006, so-called “next-generation sequencers” (NGS) were developed,
in which long DNA fragments are cut into short fragments andMy research on the reproductive behavior of snails was successfully
published (*1) , and I decided to move into genomics as a graduate
student. At that time, sequencing the genome of an organism was1

sequenced in parallel without electrophoresis. By sequencing morethan millions of DNA fragments simultaneously with a single NGS,
sequencing speed and cost are dramatically reduced. NGS hasquickly become the standard for DNA sequencing. NGS has made it
possible to read short genome fragments from microbial communities
in large numbers at low cost, and the field of metagenomic analysis
has rapidly become popular. Metagenomic analysis using NGS
provides a large number of very short sequences. To estimate themember composition (phylogenetic composition) and gene function
composition of microbial communities from these new data, it wasessential to develop new bioinformatics analysis methods and software.
Therefore, I developed analysis methods and web applications thatcan use metagenomic sequencing data. I published a paper andreceived my Ph.D. After that, I stayed at Tokyo Institute of Technology
as an assistant professor and started my career as a researcher.

sequence similarity search against reference DNA sequence data toestimate the phylogenetic position of each sequence and visualizes
the aggregated phylogenetic composition for all metagenomic
sequences.
The advantage of VITCOMIC2 is its ease of use, even for beginners.
By uploading metagenomic sequence data of a microbial community,
VITCOMIC2 automatically performs the analysis and provides thephylogenetic composition in just a few minutes. All operations are
performed in a web browser, so even users who are not familiar withbioinformatics analysis can use VITCOMIC2. Our server is used forcomputation, averaging over a dozen analyses per day. Of course, Ialso use it for my own research. Now that metagenomic analysis has
become widespread, there are many other good analysis tools thatcomplement VITCOMIC2. Since phylogenetic composition data are
the basic data for metagenomic analysis, researchers now use
different tools depending on the purpose of the analysis.

Around that time (2010 or so), NGS had become widely available andthe usefulness of metagenomic analysis was better understood, so alarge amount of metagenomic sequencing data was being produced
around the world. However, the sequence data and metadata
generated from metagenomic studies were not effectively used dueto the “difficulty of reproducing the same community”. Therefore, wedecided to collect and curate the public metagenomic data anddevelop an integrated database that would facilitate microbial omics
research. In parallel, we developed analysis methods for metagenomic
sequencing data. In 2016, Prof. Kurokawa moved to the National
Institute of Genetics (NIG), and I also moved to the institute as anassistant professor. Since coming to NIG, I have continued myresearch on metagenomics and also started “ancient DNA research”,
to infer the phylogenetic relationships of organisms from several
thousand years ago using fossil-derived DNA (ancient DNA). In 2021,
I established my own lab as an associate professor, and I now
supervise graduate students while conducting several research
projects of my own.

PZLAST Enables Similarity Searches andIntegrated Databases of Metagenomes
In metagenomic analysis, the amount of data collected from several
hundred samples is enormous, exceeding a terabyte. Public nucleotide
sequence databases already contain metagenomic sequence datafrom several hundred thousand samples. Even if you want to performa sequence similarity search against terabytes of reference sequencedata, existing commonly used tools such as BLAST cannot be used
for this purpose. Therefore, we have developed a web application
called “PZLAST”. This tool searches for sequence similarity inapproximately 3.6 terabytes of amino acid sequence data derived
from existing metagenome samples(*4). These 3.6 terabytes consist of
63.6 billion predicted proteins and approximately 2.4 trillion aminoacid residues. There is almost no other sequence similarity searchtool besides PZLAST that can accurately search such a large amountof metagenomic sequence data in a few minutes.

Development of VITCOMIC andVITCOMIC2, Tools for Easy
Phylogenetic Composition Analysis

The metagenomic sequence data being produced and accumulated
daily is a treasure trove of diverse microbial genes and proteins.
However, due to the huge amount of data, there has been no tool tosearch this huge amount of metagenomic sequence data. PZLAST,
which is available online, has a very simple metagenomic sequencesimilarity search function. It can be used to search for protein
sequences similar to the enzyme that performs similar functions toexisting enzymes but differs in its active temperature, pH, etc.

I developed VITCOMIC (Visualization Tool for Taxonomic Compositionsof Microbial Communities) (*2), a tool to quickly and accurately estimate
the phylogenetic composition of microbial communities from large
metagenomic NGS data, and an improved version, VITCOMIC2 (*3).
VITCOMIC2 is an online web application that performs a rapid2maximus) was more than 3 meters tall, making it one of the largest
birds. Giant flightless birds such as ostriches and emus, and theflying birds of South America (Tinamous) belong to a group called
Palaeognathae. We wanted to infer where Aepyornis locates within
the Palaeognathae lineage using ancient DNA analysis.

We have focused on the development of these analytical tools, but inthe future, we would like to focus on the development of databasesthat will serve as the basis for different types of research. We are
already developing the “Microbiome Datahub”, an integrated
database of metagenomic data and bacterial genomes reconstructedfrom metagenomes. Bioinformatics techniques have improved inrecent years to allow the reconstruction of genome sequences frommetagenomic data, albeit imperfectly, of individual bacteria living inspecific environments. A wide variety of bacterial draft genome
sequences can now be obtained without cultivation, but these
metagenome-derived genome data are not well organized, as theanalysis methods of the data vary from paper to paper. The
Microbiome Datahub we are developing will solve this problem, andin the future, we hope to integrate metagenome-derived genome data
and the genome data from individual isolate bacteria to develop an
integrated genome/metagenome database that covers nearly all of
the bacterial diversity that exists on Earth.

Aepyornis DNA was extracted from bones preserved by a university
collaborator in Madagascar and sequenced at the NIG and otherinstitutions. Ninety-nine percent of the DNA obtained was frommicrobes. However, after removing the microbial DNA from thesequencing data, partial nuclear gene sequences and complete
mitochondrial genome sequences were obtained. Comparing thesesequences with those of known Palaeognathae, we found that theclosest relative is the kiwi, a small flightless bird that lives in New
Zealand. Since Madagascar and New Zealand were connected by acontinent in prehistoric times, it is thought that a common ancestorfrom Madagascar and New Zealand was present on both islands andevolved independently on each. We are proud of this finding, which
we believe was made possible by ancient DNA analysis.
We wanted to verify whether ancient DNA analysis of an even older
era was possible, so we analyzed brown bears. In modern Japanbrown bears live only in Hokkaido, but tens of thousands of years
ago, they also lived in Honshu. Brown bear fossils excavated from
Honshu are larger in size than bones from modern Hokkaido bears,
and it has remained unclear what lineage the Honshu brown bears
belonged to, when they arrived, and where they came from. Therefore,
we performed a similar analysis as for Aepyornis, using 32,500-year-old
brown bear fossils from Honshu. We found that the brown bears ofHonshu are an unknown lineage, distinct from the bears of Hokkaido
or any other region of present-day Japan. We also found that theexisting brown bear group from southern Hokkaido is a sister groupto the Honshu brown bear, and that the two diverged about 160,000years ago. These findings, together with the known fossil record,suggest that brown bears migrated from Eurasia to Honshu at leasttwice.

Inference of Phylogenetic Relationshipsof Extinct Animals Using Ancient DNA
In parallel, we are also studying on ancient DNA analysis, using DNA
extracted from the remains of extinct animals. Ancient DNA analysis
is similar to metagenomics in that the DNA fragments obtained areshort fragments derived from a large number of species. Ancient DNA
analysis targets DNA derived from organisms that died more than afew decades ago, but there is no clear standard for what qualifies as“ancient”. Fossil-derived DNA has been analyzed since the 1980s.
The development of NGS has accelerated this trend, and ancientgenomics of large numbers of samples is now being conducted.
Ancient DNA analysis allows us to predict the phylogenetic
relationships of extinct organisms with living organisms, and thegenetic diversity of the extinct species during different time periods.
Because the phylogenetic information of many extinct animals is
inferred only from fossil morphology, molecular phylogenies based on
ancient DNA analysis are valuable. We have so far analyzed ancient
DNA from three species: Aepyornis from Madagascar(*5), the brownbear from Honshu, Japan(*6), and the Japanese wolf(*7).

■ Sampling bones for Ancient DNA analysis in a cave in Ueno Village,
Gunma Prefecture

Having demonstrated success in analyzing ancient DNA, we next
decided to investigate the origin of the Japanese wolf. The very small
Japanese wolf, which is considered to have been endemic to Japan,
was once widely distributed in Honshu, Shikoku, and Kyushu, butbecame extinct about 100 years ago. In addition, fossil evidence
suggests that one of the world's largest wolves lived in Honshu morethan 20,000 years ago. However, the origin of the small Japanese wolf

Aepyornis, also called the “elephant bird,” was a large flightless birdthat is thought to have become extinct several hundred years ago
after humans arrived in Madagascar. The largest Aepyornis (Aepyornis3and its phylogenetic relationship to the giant wolf were not known.
We conducted ancient DNA analysis using nuclear and mitochondrial
DNA on the remains of a 35,000-year-old giant wolf and a
5,000-year-old fossil of a small Japanese wolf. We found that thesmall Japanese wolf originated from the interbreeding of the “old”(57,000-35,000 years ago) giant wolf lineage and the later(37,000-14,000 years ago) wolf lineage.

Of course, still there are limits to what one person can do, so I also
actively promote collaborative research. I am still considered a young
researcher, and I feel privileged to be in this position, because I canspend a lot of time on research and be very focused on it. However, I
try not to be too closed in my own world too much, and I enjoy actively
engaging with people from outside to exchange information and enjoy
collaborative research.
The National Institute of Genetics has more faculty members thanstudents, which is a good environment for learning and research.
Those who want to specialize in bioinformatics are all welcome.
Please feel free to knock on our door.

■ Sampling of wolf bones for DNA analysis.

We are now in the process of analyzing the ancient DNA of Naumannelephants, which lived tens of thousands of years ago. Large
numbers of Naumann elephants have been excavated from various
locations, and fossil specimens are on display in museums, but there
have been no successful genome analyses until now. We havealready obtained interesting results on their phylogenetic
relationships and are writing a paper on this topic.

Interviewer:
Naoko Nishimura, Science writer
Photographer:
Mitsuhiko Kurusu, NIG ORD

Bioinformatics Research in Japan Facesa Critical Situation

August 2022

In terms of both human resources and budget, bioinformatics researchin Japan is in a more difficult situation than in Europe, the USA, China
and other countries. Due to the recent Machine learning boom, many
students who have graduated in bioinformatics tend to choose to workin the companies that use statistical and computer science skills.
There are significant differences in salaries and benefits between
academic and Machine learning related companies for people withexpertise in large-scale data analysis and machine learning. It is alsodifficult to find long-term, stable employment as an academic
bioinformatics researcher.

■ References*1---------■ Asymmetric reproductive isolation during
simultaneous reciprocal mating inpulmonates
Biology Letters. 2009 Apr 23; 5(2): 240-3.
*2---------■ VITCOMIC: visualization tool for
taxonomic compositions of microbialcommunities based on 16S rRNA genesequences
BMC Bioinformatics. 2010 Jun 18; 11:332.

As research budgets have also been cut, we are now facing a criticalsituation for the future of life science research in Japan as a whole,including bioinformatics. I have made various efforts, such as holding
informatics analysis workshops and co-writing books on bioinformatics
analysis, to promote young scientists, but more efforts are needed toimprove the situation.

*3---------■ VITCOMIC2: visualization tool for thephylogenetic composition of microbialcommunities based on 16S rRNA gene
amplicons and metagenomic shotgun
sequencing
BMC Systems Biology. 2018 Mar 19; 12(Suppl2):30.

I have been involved in a wide range of projects and activities, working
towards my ultimate goal - to unravel the “whole microbial diversity”
through metagenomic analysis. The majority of microorganisms
remain unknown and unnamed. I would like to continue to explore therelationships between microbes, their environments, their genomes
and their ecology.

*4---------■ PZLAST: an ultra-fast amino acidsequence similarity search server against
public metagenomes
Bioinformatics. 2021 Jul 8; 37(21): 3944‒3946.

4*5---------■ Phylogenomics and Morphology of Extinct
Paleognaths Reveal the Origin and
Evolution of the Ratites
Current Biology. 2017 Jan 9; 27(1): 68-77.
*6---------■ Ancient DNA reveals multiple origins andmigration waves of extinct Japanese brownbear lineages
Royal Society Open Science. 2021 Aug 4; 8(8):210518.
*7---------■ Paleogenomics reveals independent andhybrid origins of two morphologicallydistinct wolf lineages endemic to Japan
Current Biology. 2022 Jun 6; 32(11)2494-2504.e5

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