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Rhizobacteria Communities of Phytoremediation Plant Species in Petroleum Hydrocarbon Contaminated Soil of the Sudd Ecosystem, South Sudan

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The Sudd wetland is one of the oil-rich regions of South Sudan where environmental pollution resulting from oil extraction activities has been unprecedented. Although phytoremediation is the most feasible technique, its efficacy reduces at high TPH concentration in soil. This has made rhizoremediation the most preferred approach. Rhizoremediation involves use of a combination of phytoremediation and biostimulation. The process is catalyzed by the action of rhizobacteria. Therefore, the objective of this study is to characterize rhizobacteria communities prevalent in phytoremediation species growing in hydrocarbon-contaminated soils biostimulated with cattle manure. The treatments studied were plant species only (T1), plant species and hydrocarbons (T2), plant species and manure (T3), and plant species, manure, and hydrocarbons (T4). The rhizobacteria communities were determined using pyrosequencing of 16S rRNA. In the treatment with phytoremediation species, hydrocarbons 75 g · kg−1soil, and cattle manure 5 g · kg−1soil (T4), there was a significant increase (p
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Research Article
Rhizobacteria Communities of Phytoremediation Plant Species in
Petroleum Hydrocarbon Contaminated Soil of the Sudd
Ecosystem, South Sudan
J. A. Ruley ,
1
,
2
J. B. Tumuhairwe,
1
A. Amoding,
1
O. T. Westengen,
3
and H. Vinje
4
1
Department of Agricultural Production, Makerere University, P.O. Box 7062, Kampala, Uganda
2
Department of Agricultural Sciences,CNRES, University of Juba, P.O. Box 82, Juba, Sudan
3
Department of International Environment and Development Studies (Noragric), Norwegian University of Life Sciences (NMBU),
˚
As, Norway
4
Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences (NMBU), ˚
As, Norway
Correspondence should be addressed to J. A. Ruley; janenajeb@yahoo.com
Received 23 October 2020; Accepted 10 December 2020; Published 24 December 2020
Academic Editor: Zhun Li
Copyright ©2020 J. A. Ruley et al. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
e Sudd wetland is one of the oil-rich regions of South Sudan where environmental pollution resulting from oil extraction
activities has been unprecedented. Although phytoremediation is the most feasible technique, its efficacy reduces at high TPH
concentration in soil. is has made rhizoremediation the most preferred approach. Rhizoremediation involves use of a
combination of phytoremediation and biostimulation. e process is catalyzed by the action of rhizobacteria. erefore, the
objective of this study is to characterize rhizobacteria communities prevalent in phytoremediation species growing in hydro-
carbon-contaminated soils biostimulated with cattle manure. e treatments studied were plant species only (T1), plant species
and hydrocarbons (T2), plant species and manure (T3), and plant species, manure, and hydrocarbons (T4). e rhizobacteria
communities were determined using pyrosequencing of 16S rRNA. In the treatment with phytoremediation species, hydro-
carbons 75 g ·kg
1
soil, and cattle manure 5 g ·kg
1
soil (T4), there was a significant increase (p<0.05) in rhizobacteria abundance
with the highest ASV observed in H. rufa (4980) and the lowest in S. arundinaceum (3955). In the same treatment, bacteria
community diversity was high in H. rufa (Chao1, 10310) and the least in S. arundinaceum (Chao 1, 8260) with Proteobacteria,
Firmicutes, and Actinobacteria as the dominant phyla. Similarly, in contaminated soil treated with cattle manure, there was a
significant increase (p<0.05) in abundance of rhizobacteria genera with Pseudomonas dominating across phytoremediation
species. H. rufa was dominated by Bacillus, Fusibacter, and Rhodococcus;G. barbadense was mainly associated with Luteimonas
and Mycobacterium, and T. diversifolia was inhabited by Bacillus and Luteimonas. e rhizosphere of O. longistaminata was
dominated by Bacillus, Fusibacter, and Luteimonas, while S. arundinaceum was largely inhabited by Sphingomonas. ese
rhizobacteria genera ought to be applied in the Sudd region for bioremediation.
1. Introduction
Globally, crude oil is a critical resource for national de-
velopment. e world greatly depends on oil and, as a
result, vast amount is used, transported, and stored [1].
Crude oil is number one source of energy and a primary
raw material for major industries worldwide [2].Oil re-
mains an indispensable input for sectors such as
manufacturing (as a raw material and fuel), transport
(fuel), and trade (as an export commodity), and there has
been a steady increase in global demand for crude oil over
the last decades [2, 3, 4]. Over the next two decades, Rada
and colleagues [5] anticipate that world oil demand could
even rise to 170 million barrels per day. is belief has
compelled producing countries to devise ways and means
of increasing production, transportation, and refining of
crude oil in order to meet the purported growth in de-
mand [2, 4], South Sudan inclusive [6].
Hindawi
International Journal of Microbiology
Volume 2020, Article ID 6639118, 13 pages
https://doi.org/10.1155/2020/6639118
South Sudan is one of the famous crude oil producing
countries falling 3
rd
after Nigeria and Angola in Africa [6]
and 83
rd
among the 171 oil producing countries worldwide
[7]. Oil is the lifeline of its economy for now and over the
medium term [6]. For example, between 2008 and 2011, oil
exports accounted for 98% of government revenue [6]. is
position has fundamentally changed her economy from
agriculture to industrialization. South Sudan has a pro-
duction capacity of 298,000/390,000 barrels per day [8, 9]
including Sudd wetland. Sudd is the largest wetland in the
whole world and covers 57,000 Km
2
that makes up ap-
proximately 5% of the total land area of the Republic of
South Sudan (648,000 Km
2
) [10, 11]. e area of the wetland
is larger than countries such as Switzerland, Belgium, the
Netherlands, and Singapore [12]. Owing to this enormous
size, the Sudd ecosystems are of vast socioeconomic, cul-
tural, and biological importance locally, nationally, and
internationally. is accounts for why it was designated as a
Ramsar site in 2006 [10] making it an essential nature
conservation area.
In all crude oil producing countries around the world,
during the process of crude oil production and secondary
activities such as transportation and storage, several solids,
liquids, and gaseous forms of wastes and pollutants are
generated [13]. Also, spills and discharges of petroleum
hydrocarbons (PHC) in some environments have reportedly
been caused by initial activities such as oil field development,
transportation activities such as leakages from oil pipelines
and haulage tankers, oil well waxing, and at times when
refining and petrochemical equipment is being overhauled
[14–16] contributing to gross contamination of ecosystems.
Soil contamination with PHC is a widespread problem
and has hazardous implications on both environment and
human health [17, 18]. As earlier stated, Sudd wetland is an
oil rich zone. As a result, the Sudd ecosystems are fragile and
therefore threatened by oil exploration and extraction ac-
tivities since the 1980s [19–21] with notable effects on the
environment and natives of the area. e commonly re-
ported effects by studies [20–22] include high salt content in
water, death of livestock, reduction in vegetation cover, and
outbreak of strange diseases hitherto uncommon among
people in the local communities.
Attempts to remediate hydrocarbon-contaminated soil
are a priority in national development plans of many oil-
producing countries in order to counteract the harmful
effects of PHC [23, 24]. South Sudan is not exceptional. e
techniques deployed in remediation of PHC polluted soil are
fivefold: chemical, physical, electrical, thermal, and bio-
logical [25, 26]. e use of chemical treatment involves
chemical precipitation, membrane separation, ion exchange,
carbon absorption, aqueous chemical oxidation, and sur-
factant enhanced recovery [25]. With regard to physical
treatment, the main treatment measures involve land filling,
pumping and treating, dual phase extraction as well as air
sparging, and dual phase extraction [25, 26]. For electrical
remediation, electrical principles are applied to decontam-
inate particular sites though only limited to granular type of
soil contaminated with heavy metals [25]. e thermal
methods are largely used in environments where the
contaminants are highly volatile and include in situ vitri-
fication, incineration, and electrical pyrolysis. However, the
above-mentioned techniques are not largely used at present
because they are associated with various shortcomings such
as high cost, handling of the generated excess waste, and
secondary contamination [25, 26]. is has given way to
biological remediation techniques. It is not by surprise
therefore that in recent times, in most crude oil producing
countries, biological remediation techniques are dominating
any efforts for ecorestoration of PHC contaminated soils
[27], bioremediation inclusive [25].
Bioremediation-based rhizoremediation is a biological
technology with great potential of restoring PHC contam-
inated soils [28, 29]. Rhizoremediation refers to a process in
which the PHC contaminants are degraded by bacteria in the
rhizosphere [23, 24] and uses a suite of indigenous mi-
croorganisms [30]. is approach is nondestructive and is
environmentally acceptable [28, 29, 31] making it a desirable
and sustainable technique [31]. For example, it does not
generate toxic metabolites [29]. Relatedly, Shukla and col-
leagues [32] contend that the mechanism provides a natural
corrective solution in which the synergy between roots of
phytoremediation species and resident plant growth pro-
moting rhizobacteria (PGPR) boosts secretion of root ex-
udates, production of siderophores, phytohormones, and
phosphatases. is accounts for why the approach is
regarded an effective natural remedy for ecorestoration of
polluted sites [32] leading to its popularity as a green
technology as reported elsewhere [33–35].
Compared to other soil inhabiting microorganisms,
bacteria are the most dominant and, therefore, primary
microbial communities that play a fundamental role in
biodegradation of PHC contaminants. e various genera
utilize hydrocarbons as carbon and energy sources [36]. e
degradation potential of bacteria is harnessed with bio-
stimulation using manure. For example, cattle manure
improves soil physicochemical characteristics, hence en-
abling adaptability of bacteria in contaminated soil [37].
Additionally, some manure compounds (such as nitrogen,
phosphorus, and potassium) are high-energy electron ac-
ceptors and sources of nutrients for bacteria. Although the
degradation potential of different bacteria varies [38],
studies [39, 40] have reported Acinetobacter, Pseudomonas,
Gordonia, Rhodococcus, Immundisolibacter, Luteimonas,
Alcanivorax, Marinobacter, Mycobacterium, Corynebacte-
rium, Bacillus, Ochrobactrum, Sphingomonas, and Hahella
as the most active hydrocarbon degrading genera in rhi-
zosphere. However, the abundance of these genera in the
rhizosphere of contaminated soils in the Sudd ecosystems is
unknown yet; it is essential for harnessing bioremediation.
Furthermore, Mackova and colleagues [41] have shown that
inoculation has limited efficiency to biodegrade hydrocar-
bons due to incompatibility between bacteria and plant
species. e deployment of efficient PHC biodegrading
bacteria in contaminated soils needs to be coupled with the
use of phytoremediation species that enhance their survival
and growth [42, 43]. us, detailed characterization of
rhizosphere bacteria is necessary to facilitate selection and
use of efficient PHC biodegrading species of bacteria for
2International Journal of Microbiology
inoculation during phytoremediation [44]. erefore, the
objective of this study was to determine the rhizobacteria
communities influenced by phytoremediation species
growing in cattle manure biostimulated crude oil contam-
ination soils in the Sudd region using sequences of 16S
ribosomal RNA.
2. Materials and Methods
2.1. Experimental Design. A screen house pot experiment
was conducted at Makerere University Agricultural Re-
search Institute, Kabanyolo (MUARIK), from January
2018 to April 2018 (120 days). e soil used in the ex-
periment was collected from nonhydrocarbon contami-
nated natural undisturbed land in the Sudd region as
composite topsoil samples at a depth of 030 cm.
Treatments included two rates of partially decomposed
(1.7: 0.6 : 0.8 NPK) cattle manure, two rates of crude oil,
and five phytoremediation plant species arranged in
Completely Randomised Design (CRD). Cattle manure
was applied at rates of 0 and 5 g·kg
1
soil confirmed as
economically appropriate [45], while crude oil rates 0 and
75 g ·kg
1
soil were used. e phytoremediation plant
species were (i) wild cotton (Gossypium barbadense), (ii)
Sudan grass (Sorghum arundinaceum), (iii) wild rice
(Oryza longistaminata), (iv) false sunflower (Tithonia
diversifolia), and (v) thatching grass (Hyparrhenia rufa).
ese plant species are abundant in the Sudd region [46]
and were screened and confirmed as suitable for phy-
toremediation [47].
In this study, polypropylene plastic-made pots were
used. e soil was apportioned into 5 kg pots. To ensure
that soil, cattle manure, and crude oil are mixed thor-
oughly, a metallic sheet was used as a mixing base. e
mixture was returned into the pots with perforated bases
to allow aeration. Each pot was labeled with the name of
the respective treatment. e labeled pots were left for
one week before planting. To cater for any PHC losses,
pots were placed on their lids. Any water leachate was
used to irrigate the respective pot. e lids were also
washed after every two days and the wash water used to
irrigate respective pots.
At 120 days after planting, roots were removed from the
pots. e firmly attached soil to the roots was collected from
all pots (60 treatments) and transported in an ice cooler to
the Biotechnology Laboratory of Makerere University Re-
gional Centre for Crop Improvement at Kabanyolo, Wakiso
district, Uganda, and stored at 80
o
C until extraction of
genomic DNA.
2.2. Molecular Analysis of Bacterial Communities.
Genomic DNA was extracted from 0.25 g of the rhizosphere
soil sample using DNeasy Power Soil®DNA Isolation Kit
(Qiagen Company) following the manufacturer’s instruc-
tions. Bacterial diversity was analysed using culture inde-
pendent molecular technique16S rRNA gene PCR. e
primers used in PCR reactions were 341F and 785R. A GC
clamp was added to forward primer (F). ese targeted
approximately 300 bp of hypervariable V3 region. All PCR
amplifications were performed using ermoHybaid PCR
cycler (Molecular Biology Instrumentation, Massachusetts,
USA). PCR mixtures were prepared with 5 μl of Taq buffer
10×, 2.5 mM of MgCl
2
, 200 μmol of each deoxynucleoside
triphosphate (dNTP), 20 pmol each primer, 5 μg of bovine
serum albumin, 1% of formamide and 2.5U Taq polymerase
(Roche Molecular Biochemical, Mannheim, Germany), and
sterile filtered Milli-Q water to a final volume of 50 μl. e
PCR program was as follows: denaturing step of 94°C for
3 min, followed by 35 cycles of 1 min at 94°C, annealing for
1 min at 55°C, and elongation for 1 min at 72°C, followed by a
final elongation at 72°C for 10 min.
e concentrations used for PCR were as follows: total
mixture, 25 µl; dNTPs, 50 µM; genomic DNA, 30 ng/µl; and
each primer, 10 pmol/µl. e concentration of MgCl
2
in the
reaction mixture was maintained at 1.5 mM for effective
amplification. MgCl
2
was a cofactor for Taq enzyme and
helped in adding correct dNTPs complementary to the
sequence in newly synthesizing strand by binding to dNTPs.
A second PCR reaction was performed using 5 ml of the first
PCR products as template under the same primers (GC
clamp attached to the primer U968f ) and conditions
specified for the first PCR reaction. e PCR reactions were
performed in duplicate, in order to obtain adequate DNA
amount for electrophoresis. Amplification products were
checked in 1.3% agarose gels stained with ethidium bromide
(0.1 mg/ml). is was followed by storage at 20°C and then
sending to the LGC Genomics Sequencing Centre in Ger-
many. Purified PCR products were pyrosequenced using
Illumina MiSeq by the LGC Genomics Sequencing Centre in
Germany (http://www.support.illumina.com/downloads/
bcl2fastqconversion-software-v2-19.html).
2.3. Data Preprocessing. After sequencing, demultiplexing of
all libraries for each sequencing lane was done using Illu-
mina bcl2fastq 2.17.1.14 software (folder RAW). One to two
mismatches were allowed in the barcode and read when the
barcode distances between all libraries on the lane allowed
for it. e sorting of reads by amplicon inline barcodes
(folder RAW) was done through one mismatch that was
allowed per barcode. e barcode sequence was then clipped
from the sequence after sorting and reads with missing
barcodes, one-sided barcodes, or conflicting barcode pairs
were discarded.
Clipping of sequencing adapter remnants from all reads
(folder AdapterClipped) was carried out and reads with final
length <100 bases were discarded. e primer detection and
clipping (folder Primer Clipped) was done by allowing three
mismatches per primer; pairs of primers (Fw-Rev or Rev-
Fw) were present in the sequence fragments. Whenever
primer-dimers were detected, the outer primer copies were
clipped from the sequence. e sequence fragments were
turned into forward-reverse primer orientation after re-
moving primer sequences.
2.4. Bioinformatics Processing. After primer removal and
clipping of sequences, read sequences were loaded into R
(version 3.6) and run through DADA2 pipeline (version
International Journal of Microbiology 3
1.12) [48]. e sequences were filtered and trimmed using
filterAndTrim” function. e trimming specifications were
as follows. First, truncation length (truncLen) was set to 250
bases for both forward and reverse reads. Secondly, cutoff for
maximum expected error calculated from the quality score
(maxEE) was set to 3 for both forward and reverse reads for
quality plots. e remaining parameters were held as default.
e error rate was estimated by function “learnError.”
irdly, a dereplication process was conducted with func-
tion “derepFastq.” All identical sequencing reads were
combined into one unique sequence with a corresponding
abundance equal to number of reads with that unique
sequence.
Before merging, core sample inference algorithm was
applied to data [49]. e forward and reverse reads were
then merged together to obtain full denoised sequences with
function “mergePairs.” As defaults in DADA2, merged se-
quences were only output if forward and reverse reads
overlapped with a minimum of 12 bases. e merged se-
quences were then rearranged in an Amplicon Sequence
Variant (ASV) table [50] and cleaned for chimeras with
functions “makeSequenceTable” and “removeBimer-
aDenovo,” respectively. For taxonomic classification, rec-
ommendations of Callahan and colleagues were used [50],
together with a native implementation of Na¨
ıve Bayesian
classifier method [51] using function “assignTaxonomy” still
in DADA2 package. e ASVs with chimeras were removed
from analysis using “subset_taxa” function in “Phyloseq
package (https://github.com/joey711/phyloseq).
2.5. Statistical Analysis. All statistical analyses were per-
formed in R software (V2.15.3). To estimate coverage and
sampling diversity, rarefaction curves were constructed.
Phyloseq” package calculated population diversity (Simp-
son index), evenness (Shannon index), and richness
(Chao1). To test effect of treatments on bacterial community
structures, PERMANOVA analysis using “adonis” function
in “vegan” package was performed. To ensure that PER-
MANOVA results were not affected by in-group dispersions,
an analysis of multivariate homogeneity of group dispersion
was conducted for different treatments using “betadisper
function in “vegan” package (Anderson, 2006). Differences
in bacterial community dispersion between treatments were
assessed using PERMDISP, since a significant PERMA-
NOVA result may indicate either a difference in centroids or
an unequal dispersion between treatments. Multivariate
analysis using nonmetric multidimensional scaling (nMDS)
and principal component analysis (PCA) were used to ex-
plore hierarchical structure of bacterial community com-
position under effects of different treatments. ese were
calculated from Bray–Curtis matrices using the “metaMDS
function from “vegan” package.
3. Results
3.1. Effect of Treatment on Bacterial Community Richness.
A total of 5 million high-quality paired-end reads were
generated from Illumina MiSeq platform with an average of
83,333 reads per sample (n60). e tags were obtained
with a maximum of 81,480 filtered sequences clustered to
3927 amplicon sequence variants (ASVs) of sixty samples at
3% confidence interval. Rarefaction was conducted to ap-
proximate the number of ASVs in random samples. e
rarefaction curves (Figure 1) asymptotically approached a
plateau, suggesting that the curves accurately reflected mi-
crobial community richness and indicated that the se-
quencing efforts were sufficient for this study.
PERMANOVA analysis showed cattle manure and hy-
drocarbon contamination significantly affected rhizobac-
teria community but not plant species (Table 1). e
interaction of plant species and cattle manure explained
5.1% of ASVs variation in community structure. Similarly,
interaction of plant species and hydrocarbon accounted for
9.2% of variation in ASVs. Biostimulation of plant species
for bioremediation of TPH contaminated soil with cattle
manure explained 13.4 % variation in assemblages of bac-
terial communities (Table 1).
3.2. Taxonomic Bacterial Community Composition. e se-
quences were classified into 33 phyla, 54 classes, 128 orders,
268 families, and 511 genera of bacteria at 80% bootstrap.
Treatments containing plant species and manure (T3) had
the highest number of phyla and genera. is was followed
by treatments containing plant species, manure, and hy-
drocarbon (T4), while plant species and hydrocarbon (T2)
had the least number of phyla and genera. e most and least
abundant rhizobacteria communities were noted in treat-
ments with plant species, manure and hydrocarbon (T4) and
plant species and hydrocarbon (T2), respectively. Similarly,
most and least diversities were observed in T4 (H. rufa and
T. diversifolia) and T2 (S. arundinaceum), respectively
(Table 2).
3.3. Bacterial Community Abundance and Diversity. e
richness and diversity of bacterial communities significantly
differed (p<0.000) between plant species in all tested pa-
rameters except Simpson’s index (Table 2). In all the five-
plant species, there was high abundance of bacterial com-
munities in the treatment with plant only (T1). However,
when TPH was added to plant species (T2), there was a
significant (p<0.05) decline in abundance as shown by a
drop in Chao 1 values across the five phytoremediation
species. Addition of cattle manure (T4) to the treatment
(plant + TPH) significantly increased (p<0.05) bacterial
abundance. In S. arundinaceum, the communities quadru-
pled (from 2097 to 8260); in G. barbadense, there was
multiple increase (from 2781 to 9540) and a near multiple
increase in O. longistaminata (from 3597 to 9168) and
H. rufa (from 4304 to 10,310), while in T. diversifolia, the
communities doubled (from 4223 to 9795).
e sudden rise in abundance of bacteria communities
in the treatment with plant species, hydrocarbon, and
manure (T4) was attributed to addition of cattle manure.
Largely, manure improves soil physicochemical properties
leading to improved conditions for plant and microbial
growth. erefore, the rhizosphere became a hotspot for
4International Journal of Microbiology
survival of different bacteria communities thereby ac-
counting for the increased abundance. Moreover, cattle
manure contains bacteria strains, which could have en-
hanced biodegradation of the TPH. In all phytoremediation
plant species, there were significant differences (p<0.05) in
diversity in the Shannon index. However, the diversity in the
Simpson index was not significant (p<0.05) across all
treatments. e most abundant phylum was Proteobacteria
across all plant species with or without manure and the TPH
accounting for about 41.6% of all ASVs, followed by Acti-
nobacteria (12.7%) and Firmicutes (9.8%), of all ASVs
(Figure 2).
200
0
Species richness
600
400
600
400
200
0
5000
010000 15000 20000 2000010000 1500050000
2000010000 1500050000
Sequence sample size
Gossypium barbadense Tithonia diversifolia Oryza longistaminata
Sorghum arundinaceum Hyparrhenia rufa
T2
T2
T2
T1
T1
T1 T4
T4
T4
T1 T1
T2 T2
T4
T4
T3
T3
T3
T3
T3
aa
aT1
T2
Treatment
a
aT3
T4
Figure 1: Rarefaction curve showing sampling depths across the five plant species with and without compost and petroleum contamination
(T1 plant species only, T2 plant species and hydrocarbon, T3 plant species and Manure, and T4 plant species, manure, and
hydrocarbon).
Table 1: PERMANOVA analysis of interaction effects of plant species, organic manure, and hydrocarbons on bacterial community based on
Bray–Curtis dissimilarity.
Factor Df SS MS F. Model R
2
Pr (>F)
Plant species 4 0.5899 0.5987 3.9978 0.02941 0.081
Plant species: manure 1 0.9233 0.32611 3.0066 0.05130 0.009
Plant species: hydrocarbon 1 0.6157 0.18444 1.5462 0.09255 0.001
Interaction 4 0.9845 0.3217 2.2381 0.13421 0.002
Residuals 95 13.1882 0.13977 0.80211
Total 105 15.3171 1
Df degrees of freedom; SS sum of squares; MS mean squares; F. Model F-test value for model; R
2
R-squared; Pr (>F) pvalue.
International Journal of Microbiology 5
Proteobacteria, Firmicutes, and Actinobacteria domi-
nated TPH contaminated soils across all plant species
(Figure 2). For example, G. barbadense was mainly associ-
ated with Proteobacteria and Actinobacteria. e rhizo-
spheres of T. diversifolia and O. longistaminata were
inhabited by Proteobacteria and Firmicutes. Similarly, the
rhizosphere of S. arundinaceum was dominated by only
Proteobacteria, while the roots of H. rufa had a high
abundance of Proteobacteria, Firmicutes, and
Actinobacteria.
3.4. Rhizobacteria Genera. e dominant genera across all
phytoremediation species were Pseudomonas (Figure 3).
However, it was more dominant in H. rufa. Generally,
besides Pseudomonas, other genera observed in all phy-
toremediation species were Luteimonas, Sphingomonas,
Mycobacterium, Bacillus, and Fusibacter. ese were
relatively more abundant in manure treated hydrocar-
bon-contaminated soil (T4) (Figure 3). Compared to the
rest, H. rufa had more Bacillus,Fusibacter, and Rhodo-
coccus. Plant species G. barbadense was mainly associated
with bacteria genera Luteimonas and Mycobacterium,
while T. diversifolia was inhabited by Bacillus and
Luteimonas. e rhizosphere of O. longistaminata was
dominated by Bacillus, Fusibacter, and Luteimonas, while
S. arundinaceum was largely inhabited by Sphingomonas.
ere was an increase in bacterial diversity in manure
treated hydrocarbon contaminated soil due to addition of
cattle manure (Figure 3).
3.5. Environmental Influence on Composition of Bacterial
Communities. Bray–Curtis distance nonmetric multidi-
mensional scaling (NMDS) revealed differences in com-
position of bacterial communities between hydrocarbon and
nonhydrocarbon treatments. In two hydrocarbon-contam-
inated treatments, one was with plant species and hydro-
carbon (T2) and the other with plant species, hydrocarbon,
and manure (T4), where bacterial communities clustered in
groups (see the ring in Figure 4). is was different from
nonhydrocarbon treatments: one with plant species only
(T1) and the other with plant species and manure (T3) where
bacterial communities were scattered (Figure 4).
Results from principal component analysis (PCA) also
revealed separate clustering of bacterial communities be-
tween hydrocarbon and non-hydrocarbon-containing
treatments. Irrespective of phytoremediation plant species,
bacterial communities in the treatment containing plant
species and hydrocarbon (T2) and one containing plant
species, hydrocarbon, and manure (T4) clustered separately
from one with plant species only (T1) as well as one with
plant species and manure (T3) (Figure 5). However, the
pattern of clustering was influenced by specific phytor-
emediation species, a factor explained by differences in
percentage variances for PC1 and PC2 (Figure 5).
4. Discussion
ere were significant variations (p<0.000) between
rhizobacterial communities of phytoremediation species
with and without hydrocarbon contamination. In the
Table 2: Rhizobacteria community abundance and diversity in phytoremediation plant species biostimulated with cattle manure in
hydrocarbon contaminated soils.
Treatments Parameters
Plant species Compost (t/ha) TPH (mg
kg-1 soil) ASVs Number of
phyla
Number of
genera
Abundance
chao 1
Shannon
index
Simpson’s
index
Gossypium
barbadense
002625 40 44 5600 4.93 0.87
75 1215 24 27 2781 4. 11 0.97
206935 101 81 14226 5.97 0.76
75 4595 68. 54 9540 5.09 0.84
Tithonia
diversifolia
003144 34 57 6638 5.14 0.82
75 1936 21 34 4223 4.30 0.94
207770 85 99 15891 6.25 0.73
75 4723 60 63 9795 5.24 0.81
Oryza
longistaminata
002764 49 66 5878 5.09 0.83
75 1623 30 43 3597 4.16 0.96
206289 99 80 12944 6.14 0.74
75 4408 82 58 9168 5.16 0.82
Sorghum
arundinaceum
002198 37 37 4745 4.86 0.88
75 871 23 23 2097 3.98 0.98
205371 69 65 11095 5.87 0.78
75 3955 56 43 8260 4.84 0.89
Hyparrhenia. rufa
003583 79 86 7518 5.37 0.8
75 1979 40 47 4304 4.54 0.92
209675 172 164 19701 6.55 2.89
75 4980 140 136 10310 5.64 0.75
LSD (0.05) (plant TPH compost) 181.1∗∗∗ 5.2∗∗ 2.1∗∗∗ 365∗∗∗ 0.06ns
∗∗∗0.000, ∗∗0.001, and 0.05.
6International Journal of Microbiology
treatments with plant species alone (T1), high bacterial
diversity was noted. However, when hydrocarbons were
introduced (T2), there was a great reduction in diversity.
e bacterial community shifts and eventual decrease in
richness resulted from perturbations that normally occur
in hydrocarbon contaminated soil. Past studies [52, 53]
have proved that introduction of PHC in soil reduces
bacterial diversity considerably regardless of the soil
matrix type. Nevertheless, in this study, certain bacterial
strains resilient to toxicity of PHC existed. ese must
have used TPH as a source of energy, carbon, or electron
receptors for growth. As reported earlier, across all plant
species, bacteria genera Luteimonas, Pseudomonas, and
Sphingomonas (phylum Proteobacteria), Mycobacteria
and Rhodococcus (phylum Actinobacteria) and genera
Bacillus and Fusibacter (phylum Firmicutes) were
abundant in the treatment with plant and hydrocarbon
(T2) and one with plant species, hydrocarbon, and cattle
manure (T4).
Similarly, bacterial communities in hydrocarbon-con-
taminated soil were significantly affected by biostimulation
with cattle manure (T4). e inclusion of cattle manure
posted both direct and indirect benefits for the survival of
bacterial communities. Directly, cattle manure amendments
improved soil physicochemical characteristics enabling
speedy adaptation by microorganisms. Furthermore, the
introduction of cattle manure must have increased on soil
fertility by adding soil organic carbon (SOC), total nitrogen
(TN), and NPK. is must have improved plant resilience
and performance in the PHC contaminated soil. Accumu-
lation of soil organic carbon for example not only results in
increased microbial biomass but also affects microbial
community structure and functional diversity [54]. ere-
fore, cattle manure indirectly influenced a spectacular in-
crease in the microbial diversity observed. Cattle manure
additions also improved soil pH and physical properties
(aggregation and porosity), thus creating favorable growth
conditions for microbes. Earlier studies [55–57] have shown
1.00
0.75
0.50
0.25
0.00
1.00
0.75
0.50
0.25
0.00
Gossypium barbadense
Sorghum arundinaceum Hyparrhenia rufa
Abundance
Treatment
Phylum
Acidobacteria
Actinobacteria
Bacteroidetes
Chloroexi
Firmicutes
Planctomycetes
Proteobacteria
Verrucomicrobia
N/A
Tithonia diversifolia H. Oryza longistaminata
T1 T2 T3 T4 T1 T2 T3 T4
T1 T2 T3 T4 T1 T2 T3 T4
T1 T2 T3 T4
Figure 2: Composition and distribution of bacterial phyla with 3% relative abundance across five plant spp. with and without compost and
petroleum contamination (T1 plant species only, T2 plant species and hydrocarbon, T3 plant species and manure, and T4 plant
species, manure, and hydrocarbon).
International Journal of Microbiology 7
that addition of organic manure to hydrocarbon-contami-
nated soil enhances multiplication of bacteria population.
Furthermore, addition of cattle manure improves soil fer-
tility, which is vital for sustained plant growth [56].
In the rhizosphere, the bacterial colonize the root
surfaces, compete against other microbes and form
synergestic interactions with host plants [58]. Phyla
Proteobacteria, Actinobacteria, and Firmicutes domi-
nated the treatment with hydrocarbon contaminated soil
and plant species (T2) and treatment T4 with plant
species and manure treated hydrocarbon contaminated
soil (T4). ese phyla contain members of organotrophic
microorganisms that utilize a wide range of organic
substrates perhaps including hydrocarbon. Although
bacterial strains survive best in aerobic conditions, the
three phyla also thrive well in anaerobic environments.
eir survival in anaerobic conditions is guaranteed by
secretion of intracellular and extracellular enzymes which
help in biodegradation of recalcitrant and organo-
pollutants. ese bacteria have enzymes capable of
assimilating, degrading, and utilizing different hydro-
carbon constituents as sources of carbon and energy
[29, 58].
Assimilation is a complex biological oxidation process
enhanced by supplementation with fixed nitrogen, phos-
phate, and other nutrients [58]. For example, one of the
enzymes, oxidoreductases, enables oxidative coupling to
take place enabling both phyla to extract energy via energy-
yielding biochemical reactions which cleaves chemical
bonds, assisting transfer of electrons from a reduced organic
substrate (donor) to another chemical compound (accep-
tor). In this process, contaminants are finally oxidized to
harmless compounds. is guarantees survival of the bac-
teria communities in a less toxic environment. Furthermore,
oxidoreductases catalyze humification of various phenolic
substances in soil environment through polymerization and
copolymerization with other substrates [59].
e three phyla are also known for secreting oxygenases.
In the test samples, oxygenases both monooxygenases and
dioxygenases could have been secreted by the phyla.
Gossypium barbadense
Sorghum arundinaceum Hyparrhenia rufa
Tithonia diversifolia
Oryza longistaminata
Genus
Anerolinea
Bacillus
Candidatus_Udaeobacter
Fusibacter
KCM-B-112
Luteimonas
Mycobacterium
Phenylobacterium
Proteiniphilum
Pseudomonas
Reyranella
Rhodococcus
Romboutsia
Immundisolibacter
Sphingomonas
N/A
1.00
0.75
0.50
0.25
0.00
1.00
0.75
0.50
0.25
0.00
T4
T3
T2
T1 T4
T3
T2
T1
T4
T3
T2
T1 T4
T3
T2
T1
T4
T3
T2
T1
Abundance
Treatment
Figure 3: Variation in bacterial genera within rhizosphere of five phytoremediation species under four different treatments (T1 plant
species only, T2 plant species and hydrocarbon, T3 plant species and manure, and T4 plant species, manure, and hydrocarbon).
8International Journal of Microbiology
Monooxygenases catalyze desulfurization, dehalogenation,
denitrification, ammonification, hydroxylation, biotrans-
formation, and biodegradation of various aromatic and
aliphatic compounds, while dioxygenases introduce mo-
lecular oxygen into their substrate [60]. erefore, both
processes must have aided transformation of aromatic
precursors into aliphatic products that are less toxic, creating
better living environmental conditions. Furthermore, Pro-
tobacteria, Actinobacteria, and Firmicutes are known for
secreting lacasses [61] that serves as a catalyst for the rapid
oxidation of phenolic and aromatic substrates. Besides,
lacasses also enhance reduction of molecular oxygen to
water [62, 63]. Equally, lacasses decarboxylate phenolic and
methoxy-phenolic acids into nutritious compounds for
bacteria [64].
Results from NMDS and PCA showed clustering of
bacteria in hydrocarbon contaminated soil with plant species
(T2) and one biostimulated by manure (T4), while in
nonhydrocarbon contaminated soil with plant species only
(T1) and one with plant species and manure (T3), the
communities of bacteria were scattered from each other. e
clustering could be associated with catabolic potential of
dominant bacteria phyla established by this study. Although
Sutton [53] reasoned that regardless of soil matrix type, clean
samples (nonhydrocarbon contaminated) have higher di-
versity than contaminated soil, results of this study showed
more diversity and clustering in hydrocarbon contaminated
treatments compared to those without. e clustering must
have occurred due to the ability of the treatments with TPH
to selectively stimulate bacterial propagation especially
through addition of carbon (mixture of aliphatic and aro-
matic hydrocarbons) that enriches taxa by serving as growth
substrates [65]. e metabolic capacities of taxa therefore
enabled biotransformation of various organic compounds
by breaking down their bigger molecules into smaller units
either by oxidation to release energy or complete utilization
in other anabolic reactions. e versatility of taxa to use both
saturated aliphatic and aromatic hydrocarbons played key
role in enhancing survival and, consequently, removal of
heterogeneous toxic contamination. is scenario has been
observed in past studies. For example, Peng and colleagues
[66] concluded that oil-polluted soils support a cornucopia
of bacterial communities due to their richness in organic
matter.
Addition of cattle manure to treatments with TPH in-
creased clustering of taxa. Biostimulation with cattle manure
boosted growth performance of the rhizosphere of phy-
toremediation plant species. e associated exudates were
colonized by taxa leading to increased clustering as observed
in treatments with plant species and hydrocarbon (T2) and
plant species, hydrocarbon, and cattle manure (T4) (see
Figure 4). is concurs with Praeg [56] that rhizosphere
zones of plants are hotspots for microbial growth, abun-
dance and diversity due to nutrient availability.
5. Conclusion and Recommendation
Plant species growing in TPH contaminated soil are
inhabited by various strains of rhizobacteria because their
roots provide excellent living conditions. In this study,
Treatment
T1
T2
T3
T4
Bray NMDS
1.0
0.5
0.0
–0.5
–1.0 –0.5 0.0 0.5 1.0
NMDS1
NMDS2
Figure 4: Nonmultidimensional scaling (NMDS) showing ASVs between hydrocarbon (T2, T4) and nonhydrocarbon (T1, T3) treatments.
T1 plant species only (G. barbadense, H rufa T diversifolia, O longistaminata. and S. arundinaceum), T2 Plant species and hydrocarbon
(0, 75 g·kg
1
), T3 Plant species and manure (0, 2 tha
1
), and T4 Plant species, manure, hydrocarbon.
International Journal of Microbiology 9
rhizobacteria genera Bacillus, Fusibacter, Luteimonas, My-
cobacterium, Pseudomonas Rhodococcus, and Sphingomonas
were abundant in rhizosphere of phytoremediation species.
In the same vein, the study also established that addition of
cattle manure enhanced multiplication of these genera.
erefore, it is concluded that, in order to achieve better
PC1 (48.5% explained var.)
5025–25
–75
–50
–25
25
0
0
Tithonia diversifolia
T1
T2
T3
T4
PC2 (18.5% explained var)
(a)
PC1 (50.0% explained var.)
–50
–50
–75
25
–25
Oryza longistaminata
–100 0
0
T1
T2
T3
T4
PC2 (17.1% explained var)
(b)
PC1 (48.5% explained var.)
75
50
25
–25
–50
–50 50
0
Sorghum arundinaceum
0
T1
T2
T3
T4
PC2 (17.4% explained var)
(c)
PC1 (54.7% explained var.)
4020–20
–25
50
25
0
0
Hyparrhenia rufa
T1
T2
T3
T4
PC2 (25% explained var)
(d)
PC1 (45.1% explained var.)
Gossypium barbadense
–40 40 80–80
PC2 (21.9% explained var.)
0
–20
40
0
20
T1
T2
T3
T4
(e)
Figure 5: Principal component analysis of bacterial communities across different phytoremediation species growing under different
treatments (T1, plant species only; T2, plant species and hydrocarbon; T3, plant species and manure; T4, plant species, manure, and
hydrocarbon).
10 International Journal of Microbiology
bioremediation, TPH contaminated soils should be bio-
stimulated with cattle manure to increase rhizobacteria
richness. With the exception of Mycobacterium (a genus that
includes dangerous pathogens), this study recommends use
of the genera listed above as an inoculum during ecor-
estoration of PHC contaminated soils in Sudd region, South
Sudan. Mycobacterium is a carrier of tuberculosis (TB)
which is a common cause of death with a prevalence rate of
257 per 100,000 people in South Sudan.
Data Availability
Data for the outputs reported in this paper are part of an
ongoing Ph.D. study and can only be availed in consultation
with the corresponding author reachable at janenajeb@
yahoo.com.
Conflicts of Interest
e authors declare that there are no conflicts of interest.
Acknowledgments
e authors acknowledge support of the Ministry of pe-
troleum and Gas, Dar Petroleum Company Ltd., Sudanese
Petroleum, and other associated laboratories and colleagues
at University of Juba for valuable comments. e authors
also acknowledge the support of NORHED Project Imple-
menters, Dr. Busulwa Henry and Dr. Bojoi Moses Tomor, of
Makerere University and University of Juba, respectively.
is study was funded by NORAD through the Sudd project
(NORHED Project no. SSD-13/0021) implemented by
University of Juba, Makerere University, and the Norwegian
University of Life Sciences, NMBU.
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International Journal of Microbiology 13
... Involvement of bacterial hormones in stimulating plant growth was detected both under optimal and stressful conditions and was due to bacterial effects on plant hormonal status observed in a number of experiments with plants subjected to drought and salinity (Arkhipova et al. 2007Cheng et al. 2007;Habib et al. 2016). Importance of bacterial hormone production for the interaction between plants and bacteria has been noted in several reviews describing remediation of oil-contaminated soils (Gkorezis et al. 2016;Correa-García et al. 2018;Murray et al. 2019;Ruley et al. 2020). Concentrations of hormones [auxins and abscisic acid (ABA)] in leaves and roots of Carex hirta were affected by soil contamination with petroleum hydrocarbons (Terek et al. 2015). ...
... Indeed, in the present experiments, bacterial treatments of plants led to a more efficient degradation of oil, and its residual amounts were lower in the presence of plants treated with bacteria than in the soil, where untreated plants were growing. These results are in accordance with reported data showing that collective action of plants and their associated microorganisms is advantageous for remediation of PHC contaminated soil in terms of degradation of petroleum hydrocarbons (Gkorezis et al. 2016;Dhote et al. 2017;Ruley et al. 2020). Nevertheless, when Enterobacter sp. ...
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Maintenance of active plant growth is important for successful phytoremediation of soil contaminated with petroleum oil products. Strains of oil-degrading bacteria introduced into rhizosphere were found to reduce the extent of plant growth inhibition resulting from petroleum stress. The effect was due to combining the capacity for petroleum degradation with promotion of plant growth by bacterial phytohormones. The purpose of this work was to compare the relative importance of these mechanisms in supporting the growth of barley plants against the background of oil pollution of the soil. Plants were treated with bacterial suspensions of four strains capable of petroleum degradation and production of indole acetic acid (IAA, plant hormone of the auxin class). The strains were shown to differ in their ability to support plant growth under conditions of oil pollution. Introduction of bacteria into soil accelerated petroleum degradation. Nevertheless, oil degradation was not the only mechanism behind promotion of plant growth, since the strain with the lowest ability to degrade oil was characterized by a relatively high growth-stimulating activity. The highest ability to stimulate plant growth was detected in the case of strains, which were the most effective in increasing the concentration of IAA in plants and decreasing the stress-induced accumulation of abscisic acid (ABA).
... Henceforth, The employment of suitable microbial species can boost metal phytoavailability while reducing toxic effects, stimulating the host plant's ability to generate more biomass while storing significant concentrations of metals and decreasing metal toxic effects. Enhancing plant-rhizosphere bacterial relations can be a core part of phytoremediation technologies (Ruley et al., 2020). Innovative phytoremediation systems for the treatment of wastewater have been developed as a result of recent advancements in ecological science and engineering (Sharma et al., 2021e;Chen et al., 2016). ...
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... These microbes were isolated from an offshore oilproducing well, a wastewater digester, a drain at the bottom of a corroded kerosene storage tank and a mesothermic Tunisian spring, respectively. Some studies reported that the genus Fusibacter was predominant in petroleum hydrocarbon contaminated soil [5], arsenic biotransformation in aquifers [6] and polluted river sediments [7]. By taxonomic query on IMNGS ( www. ...
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