Using ASAR for Analysis of Electrogenic and Human Gut

Microbial Communities

Igor Goryanin

1,2 a

, Anatoly Sorokin

and Olga Vasieva

Okinawa Institute Science and Technology, Okinawa, Japan

University of Edinburgh, Edinburgh, U.K.

Ingenet Ltd, U.K.

Keywords: Metagenome Analysis, Pathogens, Human Microbiome, Bioelectrical Systems.

Abstract: In this paper we describe applications of our ASAR package to functional, taxonomic and pathways analysis

of metagenomes and propose future plans and perspectives. To illustrate an analytical potential of ASAR, we

discuss outcomes of several projects. The main focus is made on metabolic plasticity of electrochemically

active microbial communities and a potential role of integrated symbiotic bacterial interactions;

antipathogenic properties of BES, manifested in its capacity to remove some pathogens from waste streams;

and medical applications of this technology. We present ASAR-based metagenome analysis of evolving

bacterial community from distillery waste over period of 36 months in BES environment as an example.

Application of ASAR to personalised analyses of gut microbiome (GM) and the data interpretation based on

publically available association studies are also discussed in this publication.

1 INTRODUCTION

For last years, we have been engaged in development

of Bioelectrochemical Systems (BES)/Microbial Fuel

Cell (MFC) technology for wastewater treatment. The

BES/MFC applies complex interactions between

microbial populations and electrodes to remove

organics and to generate electricity (Gajda et al,

2018). By utilizing biological, chemical, engineering,

and bioinformatics approaches, wee seek to improve

BES/MFC systems for better treatment efficiencies

and electricity generation by understanding and

building almost ideal microbial communities and

developing cost-effective materials.

For better understanding of underlying biological

processes, we have created pipeline for metagenome

analysis. We have developed a new software,

Advanced metagenomic Sequence Analysis in R

(ASAR) (Orakov et al, 2017), which allows

simultaneous analysis and visualization of

taxonomic, functional, and pathways profiles of

bacterial communities from the metagenome data.

We have used ASAR to describe and improve

https://orcid.org/0000-0002-8293-774X

https://orcid.org/0000-0001-6236-6452

https://orcid.org/0000-0002-0047-0606

complex microbial communities and biofilms in

BES/MFC. The ASAR package is available for

researchers worldwide via GitHub. Statistical data

analysis software has been integrated into the ASAR

SA package, which includes capabilities to: plot

Principle Coordinates Analysis (PCoA), perform

distributed stochastic neighbour embedding (t-SNE),

and to retrieve statistics estimated through the use of

the pairwise permutational analysis of variance

(PERMANOVA).

We have also developed flat FBA modelling

software for community metabolomics studies and

integrated it into the ASAR package

(https://github.com/lptolik/asar_fba). Our ASAR DB

(Orakov et al, 2017) includes more than 400

metagenomes and is the largest in the world

electrogenic metagenomes proprietary database.

Via systematic analysis and recording of multiple

samples we also found a range of species within the

anode communities possessing the capacity for

extracellular electron transfer, both via direct contact

and electron shuttles and were able to detect

differential distribution of bacterial groups on the

Goryanin, I., Sorokin, A. and Vasieva, O.

Using ASAR for Analysis of Electrogenic and Human Gut Microbial Communities.

DOI: 10.5220/0009193602530259

In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 3: BIOINFORMATICS, pages 253-259

ISBN: 978-989-758-398-8; ISSN: 2184-4305

253

carbon cloth and activated carbon granules of the

anode surface (Kiseleva et al, 2015a). We have

successfully applied our tools for identification and

isolation of a new bacterial strain of Thalassospira HJ

(Kiseleva et al, 2015b). Using computational pathway

analysis and metabolic engineering, we have recently

constructed a novel strain of electrogenic bacterium,

Arcobacter butzleri, which allows single analyte

(lactate and acetate) detection and can be used as a

biosensor (Szydlowsky et al, 2020).

Back, in 2015, we have pioneered with taxonomic

and functional analysis of MFC communities from

different geographical location. Taxonomic analysis

showed that Proteobacteria, Bacteroidetes and

Firmicutes were abundant in AD sludge from distinct

climatic zones and constituted the dominant core of

the MFC microbiomes. Functional analysis revealed

species involved in degradation of organic

compounds commonly present in food industry

wastewaters (Kiseleva et al, 2015 a).

Accumulation of methanogenic Archaea was

observed in the electrogenic biofilms, suggesting

competition (Georg et al, 2019, Kaur et al, 2014a,b)

or rather a symbiotic relationship between

electrogenes and methanogens and a possibility for

simultaneous electricity and biogas recovery from

one integrated wastewater treatment system

(Kiseleva et al, 2015a). Using our metagenomic

approach we described the microbial diversity of the

MFCs planktonic and anodic communities derived

from two distinctively different inocula (Kiseleva et

al, 2015a) to illustrate a consistency of the MFC

community structure. Though two different archaea

species, M. barkeri and M. thermautotrophicus,

increased in the bacterial communities of swine and

biogas waste inoculated MFCs, respectively (Vasieva

et al, 2019), presence of Proteobacteria (mostly

Deltaproteobacteria) phylum and eight Geobacter

genus species as the predominant taxa in both MFCs

anodic communities have been demonstrated.

Functional analyses of metagenomes from our lab

scale experiments was sufficient to reveal metabolic

changes between different species of the MFC

dominant genus, Geobacter, suggesting that optimal

nutrient utilization at the lowest electrode potential is

achieved via genome rearrangements and a strong

inter-strain selection, as well as adjustment of the

characteristic syntrophic relationships. These

observations show a certain degree of metabolic and

genomic plasticity of electrochemically active bacteria

and their communities in adaptation to adverse anodic

and cathodic compartments (Szydlowski et al, 2019).

To study a functional adaptation of the

electrogenic bacterial community in more detail we

have constructed a lab scale and enhanced pilot-scale

reactor for nitrate removal in BES. Under applied

potentials, BES biofilms were dominated by

autotrophic denitrifying bacteria with a potential to

accept electrons from the electrode (bacteria genera

of Galionella, Sideroxydans, Thiobacillus) and

heterotrophic bacteria that are capable to accept

electrons from Fe2+ (bacteria genus of Thauera).

Bacterial community analysis based on shotgun

sequencing from the 3-electrode reactors has

confirmed metabolic adaptation of the

electrochemically active bacterial communities to

distinct anodic and cathodic environments.

Functional analyses of metagenomes suggests that

optimal nutrient utilization at the lowest electrode

potential is achieved via genome rearrangements and

a strong inter-strain selection. NADH-quinone

oxidoreductase (nuoB/C/G/L, nuoD. nuoH genes) and

NADH-ubiquinone oxidoreductase (nad3) genes

show the strongest dependence on the applied

potential and their abundancy evolves strongly over

the period of the experiment (Szydlowski et al, 2019).

We have also demonstrated that such evolution

was correlated with functional enrichment in

metagenomes of genes encoding for particular motile

(

motB, flgEF, fgrM) factors and diminishing presence

of genes encoding for virulent factors of several taxa,

especially Enteronacteriacea (Shiegella, Vibrio) and

Firmicutes (Enterococcus, Clostridia, Listeria)

(Vasieva et al, 2019, Ieropoulos et al, 2017).

The projects outlined here aim to demonstrate

capabilities of the ASAR-based approach in

taxonomic and functional analysis of bacterial

communities and detection of the communities’

adaptive processes at the genomic level.

2 EXAMPLE. METAGENOME

ANALYSIS OF DISTILLERY

WASTE MFC

2.1 Experimental Setup

This study was conducted at the Mizuho Shuzo

Awamory Distillery Ltd., in Okinawa, Japan.

Metagenomics changes that occur during the

initiation period of a 60 L serpentine-channelled MFC

treating awamori distillery wastewater at a four-day

retention time (0.54 L h

-1

) at a constant 27˚C in the

laboratory were previously reported (Kiseleva et al,

2015a). Within the first 70 days of operation the MFC

achieved 80% COD removal (2 kg COD m

-3

-1

). In

this study we performed a three-year operation of a

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254

multiple-MFC systems deployed at an awamori

facility, operating at a similar flow rate but under

ambient environmental conditions. Chemical analysis

was carried out at the Okinawa Prefecture

Environmental Science Centre.

• Staged installation of 3 tray modules with

serpentine flow, air breathing cathode and

composite activated carbon granule & glassy

carbon cloth anode.

• Each tray module split into two 21L volumes,

total module volume 50L

• Microbial Fuel cell cathode assembly, operated

without catholyte. Pat No: US 8846220 B2

• Modules fed continuously from pilot site storage,

distillery wastewater ratio increased to raise BOD

• pH adjusted manually in dosing tank to pH 6.8 – 7

• Modules underwent retrofitting several times

during operation to increase feed inlets, improve

function

• Nearly 3 years continuous operation

The observed steady increase in power production

over time was consistent with previous reports

showing that MFC power production correlates with

the thickness of the anode-colonizing biofilm (Nevin

et al, 2008). No evidence of longer-term operation

leading to a state of biofilm “exhaustion” in which the

performance of the electrogenic community declines

(Kassongo et al, 2011) were found for this particular

settings.

2.2 Bioinformatics Analysis

Whole genome sequences and 16S sequences were

initially analysed using custom-developed pipeline,

as described elsewhere (Orakov et al, 2017, Menze et

al, 2016), as well as functional analysis using

PALADIN (only applicable to WGS) (Westbroo et al,

2017). To study the selective enrichment of different

samples, PCoA analysis was performed (Anderson,

2001), and plots were generated using EMPeror

online tool. Compositional analysis of the community

was performed in R version 1.4. (Vázquez-Baeza et

al, 2013) with package compositions. Relative

abundance was represented as composition with

absolute geometry (rcomp). One-way ANOVA was

conducted to verify significant difference in

abundances of taxa between reactors (van den

Boogaart et al, 2016). For visualization purposes, five

most abundant genera in the inoculum and five most

abundant genera at the final week sample were

selected. PERMANOVA analysis was performed

with Adonis function from vegan R package

(Oksanen et al, 2018).

Functional (SEED/RAST) (Overbeek et al, 2005),

taxonomic and KEGG Ontology (Kanehisa, 2000)

annotations of reads tagged with md5 IDs from MG-

RAST together with sample metadata, functional and

taxonomic annotation hierarchy trees were generated

and downloaded. Next, functional and taxonomic

annotations were merged by identical md5’s

corresponding to unique read sequences. Then read

counts were summed for reads with same function and

taxon. Functional and taxonomic read annotations to

lowest level were matched to lowest level annotations

in their corresponding hierarchy trees to generate the

whole phylogeny of each read. The result is the 3D

dataset with axes of Functions, Taxonomy and

Metagenome samples with hierarchy for former two.

Our post-annotation analysis and visualization

tool ASAR (Orakov et al, 2017) uses data integration

algorithm to merge taxonomic and functional data

annotated at read level. The resulting 3D dataset with

axes of Functions, Taxonomy and Metagenome

samples is visualized via three heatmaps of each axis

versus two others (F&T, F&M, T&M). Additionally,

KEGG pathway enrichment sorting/heatmap and its

map visualization are implemented. Advantages of

the tool are:

1) Integrated functional and taxonomic analysis;

2) Comparative analysis of pathway enrichments;

3) KEGG pathway maps visualization.

The heatmaps show log abundance of reads

annotated with selected function in particular taxon

within particular community. On the KEGG map

each functional box is split into sections

corresponding to analysed bacterial communities.

Relevant abundancy of each function in each

community is colour coded from green (the lowest) to

dark red (the highest proportion in the community).

2.3 Results

After 18 months of bacterial community evolution

(Fig. 1) sequences associated with ‘Electron donating

reactions’ and ‘Reverse electron flow’ functions have

increased in abundancy only in the anodic

metagenomes.

A following list of functional categories was

associated with sequences which abundance

increased in all MFC chambers (Fig.1):

 Arginine-Urea cycle

 Heat shock

 Riboflavin, FMN, FAD

 Fatty acids metabolic cluster

 Organic acids

 Electron accepting reactions, NAD and NADH

 Oxidative stress

Using ASAR for Analysis of Electrogenic and Human Gut Microbial Communities

255

 Central carbohydrate metabolism

 Fermentation

 One carbon metabolism

Figure 1: Relative abundances of reads (log scale) mapped

to bacterial genomes in initial inoculum and in established

MFC communities, generated via the ASAR taxa to

samples function (level 3, max mapper (Orakov et al,

2017)). Log abundance is shown for reads annotated with

selected functions in merged taxa within the metagenomes

from anodic and planktonic communities from different

MFC chambers after 18 months of initial bacterial

community evolution.

After three years of cultivation several bacterial

families became dominating and are specifically

enriched in anodic metagenomes: Geobacteriaceae,

Syntrophoceae, Methanobacteriaceae. We also have

noticed, that families of Clostridiaceae,

Bacteroidoceae, Azonexoceae are increased mainly in

chambers’ metagenomes. At the level of genera the

genomic presentation of following became obviously

abundant in MFC (independently on a particular

MFC’s location): Sytrophobacter, Syntrophus,

Geobacter, Clostridium, Desulfovibrio, Bacteroides,

Methanothermobacter, Thiobacillus, Dechloromonas,

Metahnosphaera, Metahnobrevibacter, Metahnotrix,

Pelobacter, Desulfobacillum. Syntrophobacter,

Syntrophus, Geobacter were stronger presented in

anodic metagenomes. Abundances of genomic

sequence presentation of the following genera were

decreased in anodic metagenomes: Dechloromonas,

Clostridum, Bacteroides, Methanoregula. Here the

difference between the reference (s11) and the MFC

metagenomes became very obvious. (Fig.2)

Using Canberra PCoA method (Fig. 3) we

demonstrate a progressive change from the 3 month

community to 18 months community with 36 month

community reversing to positions between 6 and 18

months data points. References data points are close

to 6 months community ones or correspond to the

stage before the 3 month community (close to the

inoculum). Sludge reference data point is placed in

between 18 and 36 months communities’.

Organic acids metabolism and fatty acid

biosynthesis were among the most differentially

expressed between the anodic samples from different

stages of cultivation and in compare to the inoculum

references. It is well presented in the corresponding

KEGG maps. For instance, Fig. 4 presents the KEGG

map for Butanoate metabolism for Geobacteriaceae

family. One can see changes associated with particular

evolutionary time points for 5 key functions.

Figure 2: Relative abundances of reads (log scale) mapped

to bacterial genomes in initial inoculum and in established

MFC communities, generated via the ASAR taxa to

samples function (‘sum’ option mapper (Orakov et al,

2017)). Log abundance is shown for merged reads

annotated for selected taxa within the metagenomes from

anodic and planktonic communities from different MFC

chambers after 18 months of initial bacterial community

(ref) evolution.

3 DISCUSSION

The results of the ASAR-based analysis of the

metagenomes have been implemented in bio-

technological projects that lead to optimisation of the

MFC regimes and the bacterial strains, as well as

generation of new hypothesis, which are awaiting

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experimental validations. Our findings pointed to a

potentially antipathogenic property of MFC and

suggested that electrochemical metabolism may be

utilized to supress pathogenic bacteria without

triggering a spread of antibiotics resistance (Vasieva

et al, 2019, Ieropoulos et al, 2017). The highest loss

among pathogenic genera was recorded for

Enterobacteriaceae family (such as Yersinia, Vibrio,

and Shigella). The abundance of virulent genes

responsible for adhesion, secretion systems, invasion,

and intracellular survival, as well as antibiotic

resistance associated with Firmicutes and

Actinobacteria phyla of Gram positive bacteria, also

decreased in the MFC residential metagenomes

(Vasieva et al, 2019).

Figure 3: PCoA analysis for integrated taxonomic and

functional data from metagenomes presenting 2 reference

and 3, 6, 18, 36 months of bacterial community evolution.

Figure 4: Butanoate metabolism. KEGG map for

Geobacteriaceae reads enrichment in anodic communities.

Different colours of parts of each block reflect levels of

abundancies of the corresponding sequences in

metagenomes from different community evolution time

points (as indicated in the inserted legends).

Functional coupling and comparative genomics

analysis have been applied to study functional

associations of Enterococcal cAD1 sex pheromone

precursor (P13268, cad) and its orthologs, known to

be responsible for cell clumping, biofilm formation

and conjugative plasmid transfer associated with

bacterial antibiotics resistance. Our analysis of

genomic neighbourhood, motifs and phylogeny of

cad shows that the cAD1 sex pheromone peptide

release may depend on the precursor’s redox

proprieties, NADH and FMN-based redox

metabolism (NADH oxidoreductase, fumarate

reductase), and a FMN insertion chaperone, flavin

trafficking facilitator ApbE (Q82Z24). We suggest a

hypothetical model linking the NADH-driven and

FMN-dependent redox metabolism and availability

of soluble cofactors with Enterococcus, Listeria,

Oenococcus and the relevant bacterial virulent

properties during the operation of MFC for a purpose

of waste waters and medical waste treatment (Vasieva

and Goryanin, 2019). The novelty of the hypothesised

association between sex pheromone release and the

redox-related enzymatic function of the precursor

lipoprotein suggests a new approach in prevention of

antibiotic resistance spread via targeting sex

pheromone processing chaperones or the cofactor

availability.

We have validated our approach on personalised

gut microbiome (GM) analysis and interpretation

based on published association studies. We have

applied the ASAR to a series of 10 sequenced GMs

from individuals of different ethnical and

geographical backgrounds, age and health groups.

The differentially presented and detectable

taxonomic and functional signatures in each GM

metagenome were used to predict the hosts’

characteristics via correlations established in

published studies, and the predictions were validated

by available individual-associated metadata. We have

tested sensitivity of the routine annotation and data

clustering pipeline to an individual and family-linked

signatures in GM structure and functionalities, when

applied to a limited number of varying samples. The

number of samples was sufficient to demonstrate 2

main types of a GM composition, based on

Bacteroides or Prevotella as the main abundant

genera; limitation of a variety of taxa as a result of

antibiotics application; clustering of family members’

GM metagenomes, both in taxonomic and in

functional space; individual signatures related to

chronic diseases and pharmacological interventions;

and elements of ethnicity related characteristics in the

metagenomes (Vasieva et al, 2019c).

Cross-application of the approach to MFC and

different from MFC’s bacterial communities (such as

Gut microbiomes) (Kaur et al, 2014, Ieropoulos et al,

2017, Vasieva et al, 2019) ensures more detailed

validation of the developed analytical methods, and

sets new standards for their improvement. With more

bacteria genes becoming functionally annotated and

Using ASAR for Analysis of Electrogenic and Human Gut Microbial Communities

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increasing understanding of metabolic logistics

within an evolved bacterial community we are aiming

to constantly refine our methods. However, it is time

to learn principles of a microbiome adaptive

evolution and the criteria and contrasts that we can

use in the analysis, now and in the future.

4 CONCLUSIONS

We have shown that our computational pipeline and

ASAR package could be successfully used in practical

applications. We have analysed electrogenic and

human microbial communities and produced novel

data used for the software validation and prove of its

capabilities. Original hypothesis were also generated

which require further experimental confirmation.

ACKNOWLEDGEMENTS

We thank OIST support of the research. In particular

OIST Biological Systems Unit members for

providing metagenome sequencing and explanation

of experimental setup.

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