
Heavy metal contamination of the environment is a primary concern in Bangladesh. This study aims to characterize a novel heavy metal tolerant strain, Bacillus anthracis FHq, isolated from the tannery effluents of Savar, Bangladesh. The strain could tolerate up to 5 mM of lead nitrate, 2.5 mM of sodium arsenate, chromium chloride, cobalt chloride, 1.5 mM cadmium acetate, and 1 mM of sodium arsenite. Whole-genome sequencing analysis revealed that the genome of the strain is around 5.2 Mbp long, and the G + C content is 35.4%. Besides, FHq has genes cadC, zntA, arsCR, czcD, and chrA, which confer lead, arsenic, cobalt, and chromium resistance, respectively. A total of nineteen other closely related and completely sequenced B. anthracis strains were selected based on average nucleotide identity along with the FHq strain for phylogenomic and pan-genome analysis. The phylogenomic analysis predicted the inter-genomic evolutionary relationship of the strain isolated from Bangladesh, and it was closely related to a strain isolated from China. Pan-genome analysis revealed that the FHq strain possesses 6045 pan genes, 3802 core genes, and 152 unique genes in its genomic content. Hence, the genetic information and comparative analysis of the FHq strain might facilitate identifying the mechanisms conferring high resistance to lead in B. anthracis strains isolated from Bangladesh.
Citation: Farhana Haque, Ishrat Jabeen, Chaman Ara Keya, Sabbir R. Shuvo. Whole-genome sequencing and comparative analysis of heavy metals tolerant Bacillus anthracis FHq strain isolated from tannery effluents in Bangladesh[J]. AIMS Microbiology, 2022, 8(2): 226-238. doi: 10.3934/microbiol.2022018
[1] | Afia Anjum, Jarin Tabassum, Sohidul Islam, A. K. M. Imrul Hassan, Ishrat Jabeen, Sabbir R. Shuvo . Deciphering the genomic character of the multidrug-resistant Staphylococcus aureus from Dhaka, Bangladesh. AIMS Microbiology, 2024, 10(4): 833-858. doi: 10.3934/microbiol.2024036 |
[2] | Alaa Fathalla, Amal Abd el-mageed . Salt tolerance enhancement Of wheat (Triticum Asativium L) genotypes by selected plant growth promoting bacteria. AIMS Microbiology, 2020, 6(3): 250-271. doi: 10.3934/microbiol.2020016 |
[3] | Ashrafus Safa, Jinath Sultana Jime, Farishta Shahel . Cholera toxin phage: structural and functional diversity between Vibrio cholerae biotypes. AIMS Microbiology, 2020, 6(2): 144-151. doi: 10.3934/microbiol.2020009 |
[4] | Ogueri Nwaiwu . Comparative genome analysis of the first Listeria monocytogenes core genome multi-locus sequence types CT2050 AND CT2051 strains with their close relatives. AIMS Microbiology, 2022, 8(1): 61-72. doi: 10.3934/microbiol.2022006 |
[5] | Ogueri Nwaiwu, Chiugo Claret Aduba . An in silico analysis of acquired antimicrobial resistance genes in Aeromonas plasmids. AIMS Microbiology, 2020, 6(1): 75-91. doi: 10.3934/microbiol.2020005 |
[6] | Momoka Terasaki, Yukiko Kimura, Masato Yamada, Hiromi Nishida . Genomic information of Kocuria isolates from sake brewing process. AIMS Microbiology, 2021, 7(1): 114-123. doi: 10.3934/microbiol.2021008 |
[7] | Alfred Mitema, Naser Aliye Feto . Molecular and Vegetative Compatibility Groups Characterization of Aspergillus flavus Isolates from Kenya. AIMS Microbiology, 2020, 6(3): 231-249. doi: 10.3934/microbiol.2020015 |
[8] | Amira ElBaradei, Dalia Ali Maharem, Ola Kader, Mustafa Kareem Ghareeb, Iman S. Naga . Fecal carriage of ESBL-producing Escherichia coli in Egyptian patients admitted to the Medical Research Institute hospital, Alexandria University. AIMS Microbiology, 2020, 6(4): 422-433. doi: 10.3934/microbiol.2020025 |
[9] | Ana M. Castañeda-Meléndrez, José A. Magaña-Lizárraga, Marcela Martínez-Valenzuela, Aldo F. Clemente-Soto, Patricia C. García-Cervantes, Francisco Delgado-Vargas, Rodolfo Bernal-Reynaga . Genomic characterization of a multidrug-resistant uropathogenic Escherichia coli and evaluation of Echeveria plant extracts as antibacterials. AIMS Microbiology, 2024, 10(1): 41-61. doi: 10.3934/microbiol.2024003 |
[10] | Karlene Lambrechts, Pieter Gouws, Diane Rip . Genetic diversity of Listeria monocytogenes from seafood products, its processing environment, and clinical origin in the Western Cape, South Africa using whole genome sequencing. AIMS Microbiology, 2024, 10(3): 608-643. doi: 10.3934/microbiol.2024029 |
Heavy metal contamination of the environment is a primary concern in Bangladesh. This study aims to characterize a novel heavy metal tolerant strain, Bacillus anthracis FHq, isolated from the tannery effluents of Savar, Bangladesh. The strain could tolerate up to 5 mM of lead nitrate, 2.5 mM of sodium arsenate, chromium chloride, cobalt chloride, 1.5 mM cadmium acetate, and 1 mM of sodium arsenite. Whole-genome sequencing analysis revealed that the genome of the strain is around 5.2 Mbp long, and the G + C content is 35.4%. Besides, FHq has genes cadC, zntA, arsCR, czcD, and chrA, which confer lead, arsenic, cobalt, and chromium resistance, respectively. A total of nineteen other closely related and completely sequenced B. anthracis strains were selected based on average nucleotide identity along with the FHq strain for phylogenomic and pan-genome analysis. The phylogenomic analysis predicted the inter-genomic evolutionary relationship of the strain isolated from Bangladesh, and it was closely related to a strain isolated from China. Pan-genome analysis revealed that the FHq strain possesses 6045 pan genes, 3802 core genes, and 152 unique genes in its genomic content. Hence, the genetic information and comparative analysis of the FHq strain might facilitate identifying the mechanisms conferring high resistance to lead in B. anthracis strains isolated from Bangladesh.
Industrial processes and various chemical compounds contain heavy metals and metalloids. The persistence of these metals and metalloids causes significant accumulation in the environment and negatively impacts animal health [1]. Human organs like the liver, lung, brain, and bones can be damaged from continuous exposure to heavy metals and metalloids. In Bangladesh, the dispersal of lead (Pb), cadmium (Cd), and chromium (Cr) in the environment are related to unplanned and rapid automation and urbanization [2]. Municipal waste, industrial effluents, pesticides, and chemical fertilizers cause heavy metals and metalloid pollution in the soil of industrial zones and rivers around Dhaka and Chattogram districts of Bangladesh. Therefore, a higher amount of lead, cadmium, chromium, and arsenic (As) were detected in these industrial zones and the tannery effluent in Bangladesh [3],[4].
Bacillus anthracis is a spore-bearing Gram-positive bacteria known for heavy-metal tolerance in different niches. Previously, several Bacillus species have been isolated from heavy metal contaminated sites [5]. The cell wall of Gram-positive bacteria serves as a natural barrier to heavy metals. Besides, teichoic and teichuronic acids present in the peptidoglycan are responsible for binding heavy metals [6]. Carboxyl and hydroxyl groups in macromolecules and bio-ligands like amide and sulfonamide are also involved in binding heavy metals in some Bacillus species [7]. The average genome size of B. anthracis is 5 to 6 megabase pairs [8]. The pan-genome of B. anthracis consists of roughly 3000 genes [9].
In this study, a strain of B. anthracis FHq was isolated from tannery effluents in Bangladesh. The objective of the study was to identify significant genes that are included in the resistance of heavy metals. In addition, the genomic database obtained from the study strain will provide insight into determining the mechanisms conferring high resistance to heavy metals of a B. anthracis strain isolated from Bangladesh. To the best of our knowledge, the whole genome sequencing data of a heavy metal tolerant B. anthracis strain FHq-isolated from Bangladesh is reported for the first time. Additionally, a comprehensive study of the metal resistance genes and a comparative analysis were conducted between the FHq strains and nineteen closely related and completely sequenced B. anthracis strains based on the average nucleotide identity (ANI) to identify unique genes for FHq.
The bacterial strain was isolated from tannery effluent of Savar, Bangladesh, following the protocol described in [10] with few modifications. The sample was collected in a sterile glass bottle and transferred to the laboratory at North South University. The sample was serially diluted (10−1 to 10−10), and 100 µL of the sample was plated on the Lysogeny Broth (LB) plates (Himedia, India) supplemented with 1mM lead nitrate (Pb(NO3)2) (Merck, Germany) and grown for 24 hours at 37 °C. Individual colonies with distinct characteristics were collected and were grown in LB broth. For further studies, these bacterial colonies were stored at -80 °C in 50% (v/v) glycerol stock.
The strain was grown at 37 °C in the LB plate for 24–36 hours, supplemented with different concentrations (1 mM, 1.5 mM, 2 mM, 2.5 mM, 3 mM and 5 mM) of lead nitrate (Pb(NO3)2), sodium arsenate (Na3AsO4) (Merck, Germany), sodium arsenite (NaAsO2) (Merck, Germany), cobalt chloride (CoCl2) (Scharlab, Spain), cadmium acetate (Cd(CH3CO2)2.2H20) (Qualikems,India) and chromium chloride (CrCl3) (Scharlab, Spain). Growth was observed after overnight incubation. LB plates without heavy metal supplementation were used as a control during each observation.
The bacterial culture was grown overnight at 37 °C for DNA extraction. DNA extraction was performed using the Wizard Genomic purification kit (Promega, USA) according to the protocol provided by the manufacturer. The Illumina DNA Prep kit (Illumina, USA) was used to prepare the library by following the manufacturer's protocol. Illumina Miniseq technology (Illumina, USA) was used for sequencing the genome (Invent Technology Ltd., Dhaka, Bangladesh). Trimmomatic was used to remove the adapters from FASTQ sequences [11]. de novo assembly of the read to the contigs was done by using the Shovill (https://github.com/tseemann/shovill) (Galaxy Version 1.0.4 + galaxy1) pipeline, and Spades assembler was utilized to assemble the genome in the Galaxy server [12]. The annotation of the draft genome was performed by using the RAST server [13] and the National Center for Biotechnology Information (NCBI) Genome Annotation Pipeline (PGAP) [14]. The data for the contigs can be found in NCBI (PRJNA668995).
The metal resistance genes were predicted from the RAST server data and compared with the genes in the BacMet database [15]. Phage Search Tool Enhanced Release (PHASTER) server was used to identify prophage sequences in the genome [16]. The PHASTER server predicts the prophage sequences according to the score on a scale of 150. Hit score > 90 is considered an intact or complete prophage sequence; < 70 is considered incomplete, and a score ranging between 70 to 90 is regarded as a questionable prophage sequence [16]. The PLSDB plasmid database was used to check the presence of plasmid [17]. The pathogenicity of the strain was checked using PathogenFinder 1.1 [18]. In every case, the draft genome sequence of B. anthracis FHq was input in FASTA format, and the default parameters of the servers were used.
A total of nineteen B. anthracis strains (S1 Table) were collected from the NCBI database based on their average nucleotide identity (ANI) (96–100%) calculated in the EDGAR software (16) (S2 Table). Later, Type Strain Genome Server (TYGS) [19] was used with the default parameter to construct the phylogenomic tree along with the B. anthracis FHq strain. TYGC used Genome BLAST Distance Phylogeny (GBDP) strategy to contract the phylogenomic tree.
Each of the nineteen Bacillus strains was analyzed using the RAST server to find the heavy metal resistance genes and compared to the heavy metal resistance genes of the B. anthracis FHq strain. Later, pan-genome analysis was performed by using Bacterial Pan-Genome Analysis (BPGA) software [20]. The BPGA software also predicted the Clustered Orthologous Groups (COG) of proteins by comparing the protein sequences of the genomes.
The unique gene sequences identified in the pan-genome analysis of FHq were further analyzed using pBLAST. The functions of the hypothetical proteins, encoded by some unique genes, were predicted using Pfam [21], HHpred [22], and Conserved domain database-CDD [23]. The Pfam server implements the Hidden Markov Model (HMM) algorithm to predict the domains. HMM is a statistical model used to describe the evolution of observable events that depend on internal factors and are not directly observable. The HHpred server builds an alignment of homologs for the query sequence by multiple iterations of PSI-BLAST searches against the non-redundant database from NCBI. The CDD uses RPS-BLAST, a variant of PSI-BLAST, to scan a set of pre-calculated position-specific scoring matrices with the given protein query.
The isolated strain was found to tolerate up to 1 mM of sodium arsenite, 1.5 mM cadmium acetate, 2.5 mM of sodium arsenate, 2.5 mM cobalt chloride, 2.5 mM chromium chloride, and 5 mM concentration of lead nitrate (Figure 1).
The genome length of FHq was calculated to be 5238597 bp, the G + C content was 35.4%, and the N50 value of the assembly was 572044 (S3 Table). The RAST server annotated the genes and divided them into 332 subsystems, where the majority of the subsystems are categorized as protein metabolism, amino acid and derivatives, and carbohydrate (S1 Figure). The RAST server also predicted that the genome contains 112 rRNAs and 5544 coding sequences (CDS) (S3 Table). No plasmid was detected by using The PLSDB database. However, the PHASTER server could predict three genome regions that contain prophage sequences (S4 Table). The first region of the sequences was similar to Phage Lister 2389, a native bacteriophage of Listeria species [24]. The second and third regions of the sequences were matched with Phage Bacill vb BhaS 171, and the Phage Bacill Waukesha92, respectively. Later, results from PathogenFinder 1.1, showed that the probability of FHq being a human pathogen is 0.782, where 1 is the highest value of probability.
Heavy metals | Genes | Functions of the proteins |
Lead | cadC | Cadmium efflux system accessory protein Function: Regulates the CadA gene involved in Pb, Cd, and Bi resistance. |
zntA | Lead, cadmium, zinc, and mercury transporting ATPase; Copper-translocating P-type ATPase Function: Activates to response stress signal in bacteria |
|
Arsenic | arsR | Arsenical resistance operon repressor |
arsC | Arsenate reductase thioredoxin-coupled, Low molecular weight phosphatases (LMWP) family | |
acr3 | Arsenical-resistance protein ACR3 | |
Cobalt | czcD | Cobalt/zinc/cadmium resistance protein CzcD |
Chromium | chrA | Chromate transport protein |
Protein BLAST (pBLAST) was performed on the genomic data from the RAST server to identify the functions of the proteins. Later, the BLAST result was compared to the BacMet database- a database for antimicrobial, biocide, and metal resistance genes. The zntA and cadC genes involved in lead resistance; and acr3, arsC, arsR genes involved in arsenic resistance were detected in the genome of FHq. Furthermore, czcD and chrA involved in cobalt and chromium resistance, respectively, were also detected in the genome of FHq (Table 1) and (Tables S5 and S7).
The CadC regulates the cadA gene; cadA gene is responsible for lead, cadmium, and bismuth resistance [25],[26]. ZntA protein has the highest selectivity for Pb2+, Zn2+, and Cd2+ [27],[28]. The acr3 gene encodes the arsenical resistance protein that works as an arsenical resistance membrane transporter [29] Besides, the acr3 gene is a part of the ars operon that contains arsC and arsR genes. The arsR gene codes ArsR protein, which is a trans-acting regulatory protein. Moreover, ArsC protein reduces arsenate [As(V)] to arsenite [As(III)] [29]. czcD is a transporter gene that influences Zn2+ and Cd2+ resistance and is required to activate the czc operon [30]. The chrA gene encodes chromate transporting protein ChrA, responsible for the inducibility of the resistance to chromium compounds [31].
The phylogenomic tree was constructed using the type strain genome server by inputting the complete genome sequences of the B. anthracis strains (S1 Table). The FHq strain belongs to a completely different branch along with the MCCC 1A01412 (Figure 2).
Pan-genomes of twenty different strains of B. anthracis were analyzed using Bacterial Pan-genome analysis (BPGA) software. Genes present in all strains of the data set are termed core genes. Genes present in some strains are the accessory genes, and the genes specific or unique for a single strain are annotated unique genes. Core, accessory, and species-specific gene families represent the pan genes in that analysis, also known as the pangenome [32]. Genes present in the other members of the dataset but absent in a particular one are exclusively absent genes. The total gene families of the compared strains range from 4744 to 6045 (S8 Table). All the strains share 3802 core gene families in the dataset. The FHq strain has the maximum number of gene families (6045) and the highest number of unique gene families (152) among all the analyzed strains in our study. In contrast, the lowest number of gene families present in the B. anthracis Ames strain was 4744. Additionally, accessory genes varied for each strain, ranging between 892 to 1116.
Later, the COG analysis of the pan-genome showed that most of the proteins in the genome, especially the core genes, are involved in metabolic activities from the pan-genome analysis (Figure 4). Most of the unique genes are involved in information processing and storage categories.
The plot indicates how the number of total gene families rises and declines in the core gene families with each consecutive inclusion of a Bacillus anthracis genome. The black regression line indicates pan-genome, and the grey regression line indicates core-genome.
Among the 152 unique gene sequences predicted in pan-genome analysis in the FHq genome, 76 (50%) genes were predicted to encode hypothetical proteins. Among the used servers, only HHpred predicted that the hypothetical protein (HP12) has structural and sequence homology with the cnrR gene-a nickel-cobalt resistant gene [33]. This cnrR gene has metal sensing and signals transduction activities towards Ni (II) and Co (II). Besides, the functions of 12 other hypothetical proteins were predicted (S6 Table). Those hypothetical proteins are involved in DNA binding, transcription regulation, and virulence.
Heavy metals and metalloid contamination are increasing worldwide, including in Bangladesh [2]. The adverse effects of heavy metals used in the industries have been known for a long time. In addition, the typical tannery wastewaters contain Pb, Cu, Fe, Na, Cr, Cd, Zn, and Ni-like heavy metals [3],[4]. Heavy metals are mixed with the nearby areas' soil and water through the tannery discharges, causing health hazards to humans, animals, plants, and aquatic lives.
This study was conducted on genotypic and phenotypic characteristics of a novel B. anthracis FHq strain isolated from tannery effluent of the Savar area, Bangladesh. The lead tolerance level of the FHq strain was double that of arsenic, chromium, and cobalt. The MIC of lead nitrate was 5 mM in the B. anthracis FHq strain. In contrast, previous studies reported that the average lead tolerance level of Bacillus species is 3 mM lead [34]–[36].
Whole-genome sequencing data of the strain FHq was found consistent with the phenotypic data obtained from our study. The genomic analysis could predict a few heavy metal tolerance genes, as described in the result section. Among all the heavy metal resistant genes, the cadC and zntA genes have been found in the genome of the FHq strain that is likely to be responsible for lead resistance (Table 1). In addition, the cadC gene encoding cadmium efflux system accessory protein regulates the cadA gene that is responsible for conferring resistance to lead, cadmium and bismuth during in vitro analysis [26]. The zntA gene codes for lead, cadmium, zinc, and mercury transporting ATPase along with copper-translocating P-type ATPase. Therefore, based on the above-mentioned discussion, a lead-resistance pathway for the FHq strain might be proposed, as shown in Figure 5.
The genome of FHq also contains arsC, arsR, and acr3 genes for arsenic; czcD for cobalt; and chrA gene for chromium resistance. The arsR gene encodes a trans-acting transcriptional repressor protein that binds to the promoter region of ars operons. The interaction of this protein with arsenite dissociates the repressor protein from the DNA and allows transcription of the operon [29]. Arsenate reductase thioredoxin-coupled enzyme from the low molecular weight proteins (LMWP) family is encoded by the arsC gene (Table 1). In B. subtilis species, the arsC gene catalyzes the intracellular reduction of arsenate to arsenite. Arsenite is then extruded from cells through an efficient and specific transport system that provides arsenic resistance [29]. Besides, chromium resistance in bacteria is primarily performed by a specific efflux system that pumps chromate out of the cell, thereby lowering the intracellular concentration [37].
The unique hypothetical proteins of the FHq strain were further analyzed. The In-silico study by the HHpred server predicted only one metal resistance gene (Denoted as HP12, shown in (S6 Table) from the hypothetical proteins. This gene has sequence similarities with the cnrR, also known as cnrX, a gene associated with metal binding, metal sensing, signal-transducing, and specifically nickel-cobalt resistance. The cnrR gene encodes CnrR protein that is found in the cytoplasm. Structurally, the CnrR protein contains six histidine residues, whose spatial arrangement in the primary amino acid sequence is identically conserved in the NccX protein. The NccX protein is a cation efflux protein involved in nickel-cobalt-cadmium resistance [38].
Among the studied strains, B. anthracis MCCC 1A01412 is the nearest neighbor of the FHq strain in the phylogenomic tree. The strain was isolated from sediment of the South China sea (S1 Table). Both FHq and MCCC 1A01412 have similar heavy metal resistant genes (S5 Table). Furthermore, a comparative study was performed on all the strains selected for phylogenomic analysis. Except for chrA (absent in the 17OD930 strain), all the other metal resistance genes identified in FHq are present in the genomes of the other nineteen strains of the dataset (S5 Table).
In the pan-genome analysis, the strain FHq carries the highest number of unique gene sequences of 152 to be exact, of which 76 genes (50%) encode hypothetical proteins. A total of 30 gene sequences out of the total 76 genes (~40%) are unique for B. anthracis species, and 46 (60%) are commonly found in multiple species of Bacillus. There are 15 phage sequences encoding phage head, tail, and portal proteins and a phage replisome organizer N-terminal domain-containing proteins commonly found in multiple Bacillus species. The rest of the unique sequences encode several enzymes, regulatory proteins, and toxins. As per the COG database, the highest number of unique genes found in the FHq strain are involved in metabolism (Figure 4). However, a significant portion of the gene codes for proteins with unknown functions.
Novel B. anthracis strain FHq revealed the presence of multiple metal resistance genes. Those metal resistance genes might be involved in the metal resistance pathways to increase the metal resistance capacity of the FHq strain compared to other B. anthracis strains. Besides, In-silico analysis of the hypothetical proteins predicts the function of a metal resistance protein. Lastly, the phylogenomic analysis imparts the evolutionary relationship of FHq with other B. anthracis strains isolated around the world.
[1] |
Abbaszade G, Szabó A, Vajna B, et al. (2020) Whole genome sequence analysis of Cupriavidus campinensis S14E4C, a heavy metal resistant bacterium. Mol Biol Rep 47: 3973-3985. https://doi.org/10.1007/s11033-020-05490-8 ![]() |
[2] | Islam MM, Karim MR, Zheng X, et al. (2018) Heavy metal and metalloid pollution of soil, water and foods in Bangladesh: A critical review. Int J Environ Res Public Health 15. https://doi.org/10.3390/ijerph15122825 |
[3] |
Jahan M, Akhtar N, Khan N, et al. (2015) Characterization of tannery wastewater and its treatment by aquatic macrophytes and algae. Bangladesh J Sci Ind Res 49: 233-242. https://doi.org/10.3329/bjsir.v49i4.22626 ![]() |
[4] | Saha B, Azam FA Bin (2021) Probable ways of tannery's solid and liquid waste management in bangladesh-an overview. Text Leather Rev 4: 76-95. https://doi.org/10.31881/TLR.2020.25 |
[5] |
Tariq AL, Sudha S, Reyaz AL (2016) Isolation and screening of Bacillus species from sediments and application in bioremediation. Int J Curr Microbiol Appl Sci 5: 916-924. http://dx.doi.org/10.20546/ijcmas.2016.506.099 ![]() |
[6] | Rajagopal M, Walker S (2017) Envelope structures of gram-positive bacteria. Currunt Top Microbiol Immunol 404: 1-44. https://doi.org/10.1007/82_2015_5021 |
[7] |
Çabuk A, Akar T, Tunali S, et al. (2006) Biosorption characteristics of Bacillus sp. ATS-2 immobilized in silica gel for removal of Pb(II). J Hazard Mater 136: 317-323. https://doi.org/10.1016/j.jhazmat.2005.12.019 ![]() |
[8] |
Kim Y, Koh I, Young Lim M, et al. (2017) Pan-genome analysis of Bacillus for microbiome profiling. Sci Rep 7: 1-9. https://doi.org/10.1038/s41598-017-11385-9 ![]() |
[9] |
Rouli L, MBengue M, Robert C, et al. (2014) Genomic analysis of three African strains of Bacillus anthracis demonstrates that they are part of the clonal expansion of an exclusively pathogenic bacterium. New Microbes New Infect 2: 161-169. https://doi.org/10.1002/nmi2.62 ![]() |
[10] | Shammi T, Ahmed S (2013) Heavy metal tolerance and antibiotic resistance of Bacillus spp. isolated from two major rivers in Bangladesh. Bangladesh J Microbiol 30. https://doi.org/10.3329/bjm.v30i1-2.28448 |
[11] |
Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120. https://doi.org/10.1093/bioinformatics/btu170 ![]() |
[12] |
Afgan E, Baker D, Batut B, et al. (2018) The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update. Nucleic Acids Res 46: W537-W544. https://doi.org/10.1093/nar/gky379 ![]() |
[13] |
Overbeek R, Olson R, Pusch GD, et al. (2014) The SEED and the rapid annotation of microbial genomes using subsystems technology (RAST). Nucleic Acids Res 42: 206-214. https://doi.org/10.1093/nar/gkt1226 ![]() |
[14] |
Tatusova T, Dicuccio M, Badretdin A, et al. (2016) NCBI prokaryotic genome annotation pipeline. Nucleic Acids Res 44: 6614-6624. https://doi.org/10.1093/nar/gkw569 ![]() |
[15] |
Pal C, Bengtsson-Palme J, Rensing C, et al. (2014) BacMet: Antibacterial biocide and metal resistance genes database. Nucleic Acids Res 42: 737-743. https://doi.org/10.1093/nar/gkt1252 ![]() |
[16] |
Arndt D, Grant JR, Marcu A, et al. (2016) PHASTER: a better, faster version of the PHAST phage search tool. Nucleic Acids Res 44: W16-W21. https://doi.org/10.1093/nar/gkw387 ![]() |
[17] |
Galata V, Fehlmann T, Backes C, et al. (2019) PLSDB: A resource of complete bacterial plasmids. Nucleic Acids Res 47: D195-D202. https://doi.org/10.1093/nar/gky1050 ![]() |
[18] |
Cosentino S, Voldby Larsen M, Møller Aarestrup F, et al. (2013) PathogenFinder-distinguishing friend from foe using bacterial whole genome sequence data. PLoS One 8. https://doi.org/10.1371/journal.pone.0077302 ![]() |
[19] | Meier-Kolthoff JP, Göker M (2019) TYGS is an automated high-throughput platform for state-of-the-art genome-based taxonomy. Nat Commun 10. https://doi.org/10.1038/s41467-019-10210-3 |
[20] |
Chaudhari NM, Gupta VK, Dutta C (2016) BPGA-an ultra-fast pan-genome analysis pipeline. Sci Rep 6: 1-10. https://doi.org/10.1038/srep24373 ![]() |
[21] |
Mistry J, Chuguransky S, Williams L, et al. (2021) Pfam: The protein families database in 2021. Nucleic Acids Res 49: D412-D419. https://doi.org/10.1093/nar/gkaa913 ![]() |
[22] |
Söding J, Biegert A, Lupas AN, et al. (2005) The HHpred interactive server for protein homology detection and structure prediction. Nucleic Acids Res 33: 244-248. https://doi.org/10.1093/nar/gki408 ![]() |
[23] |
Marchler-Bauer A, Lu S, Anderson JB, et al. (2011) CDD: A conserved domain database for the functional annotation of proteins. Nucleic Acids Res 39: 225-229. https://doi.org/10.1093/nar/gkq1189 ![]() |
[24] |
Klumpp J, Loessner MJ (2013) Listeria phages. Genomes, evolution, and application. Bacteriophage 3. https://doi.org/10.4161/bact.26861 ![]() |
[25] |
Endo G, Silver S (1995) CadC, the transcriptional regulatory protein of the cadmium resistance system of Staphylococcus aureus plasmid pI258. J Bacteriol 177: 4437-4441. https://doi.org/10.1128/jb.177.15.4437-4441.1995 ![]() |
[26] |
Jung J, Jeong H, Kim HJ, et al. (2016) Complete genome sequence of Bacillus oceanisediminis 2691, a reservoir of heavy-metal resistance genes. Mar Genomics 30: 73-76. https://doi.org/10.1016/j.margen.2016.07.002 ![]() |
[27] |
Rensing C, Mitra B, Rosen BP (1997) The zntA gene of Escherichia coli encodes a Zn(II)-translocating P-type ATPase. Proc Natl Acad Sci USA 94: 14326-14331. https://doi.org/10.1073/pnas.94.26.14326 ![]() |
[28] |
Noll M, Lutsenko S (2000) Expression of ZntA, a zinc-transporting P1-type ATPase, is specifically regulated by zinc and cadmium. IUBMB Life 49: 297-302. https://doi.org/10.1080/15216540050033168 ![]() |
[29] |
Fekih I Ben, Zhang C, Li YP, et al. (2018) Distribution of arsenic resistance genes in prokaryotes. Front Microbiol 9: 1-11. https://doi.org/10.3389/fmicb.2018.02473 ![]() |
[30] |
Anton A, Weltrowski A, Haney CJ, et al. (2004) Characteristics of zinc transport by two bacterial cation diffusion facilitators from Ralstonia metallidurans CH34 and Escherichia coli. J Bacteriol 186: 7499-7507. https://doi.org/10.1128/JB.186.22.7499-7507.2004 ![]() |
[31] |
Aguilera S, Aguilar ME, Chávez MP, et al. (2004) Essential residues in the chromate transporter ChrA of Pseudomonas aeruginosa. FEMS Microbiol Lett 232: 107-112. https://doi.org/10.1016/S0378-1097(04)00068-0 ![]() |
[32] |
Guimarães LC, Benevides De Jesus L, Vinícius M, et al. (2015) Inside the pan-genome-methods and software overview. Curr Genomics 16: 245-252. https://doi.org/10.2174/1389202916666150423002311 ![]() |
[33] |
Grass G, Große C, Nies DH (2000) Regulation of the cnr cobalt and nickel resistance determinant from Ralstonia sp. strain CH34. J Bacteriol 182: 1390-1398. https://doi.org/10.1128/JB.182.5.1390-1398.2000 ![]() |
[34] |
Ayangbenro AS, Babalola OO (2020) Genomic analysis of Bacillus cereus NWUAB01 and its heavy metal removal from polluted soil. Sci Rep 10: 1-12. https://doi.org/10.1038/s41598-020-75170-x ![]() |
[35] |
Roane TM (1999) Lead resistance in two bacterial isolates from heavy metal–contaminated soils. Microb Ecol 37: 218-224. https://doi.org/10.1007/s002489900145 ![]() |
[36] | Arifiyanto A, Apriyanti FD, Purwaningsih P, et al. (2017) Lead (Pb) bioaccumulation; Genera Bacillus isolate S1 and SS19 as a case study. Proceeding Int Biol Conf . https://doi.org/10.1063/1.4985394 |
[37] | Branco R, Morais PV (2013) Identification and characterization of the transcriptional regulator ChrB in the chromate resistance determinant of Ochrobactrum tritici 5bvl1. PLoS One 8. https://doi.org/10.1371/journal.pone.0077987 |
[38] |
Ziani W, Maillard AP, Petit-Härtlein I, et al. (2014) The X-ray structure of NccX from Cupriavidus metallidurans 31A illustrates potential dangers of detergent solubilization when generating and interpreting crystal structures of membrane proteins. J Biol Chem 289: 31160-31172. https://doi.org/10.1074/jbc.M114.586537 ![]() |
![]() |
![]() |
1. | Mohammed Jafar Uddin, Farhana Haque, Ishrat Jabeen, Sabbir R. Shuvo, Characterization and whole-genome sequencing of an extreme arsenic-tolerant Citrobacter freundii SRS1 strain isolated from Savar area in Bangladesh, 2023, 69, 0008-4166, 44, 10.1139/cjm-2022-0149 | |
2. | Qiang Li, Wenxia Yuan, Xiujuan Deng, Yaping Chen, Limei Li, Lijiao Chen, Raoqiong Che, Wei Huang, Yamin Wu, Chun Wang, Zejun Wang, Miao Zhou, Zongpei Fan, Baijuan Wang, High lead-tolerant mutant Bacillus tropicus AT31-1 from rhizosphere soil of Pu-erh and its remediation mechanism, 2025, 416, 09608524, 131751, 10.1016/j.biortech.2024.131751 | |
3. | Arunmozhi Bharathi Achudhan, Lilly M. Saleena, Comparative genomic analysis and characterization of novel high-quality draft genomes from the coal metagenome, 2024, 40, 0959-3993, 10.1007/s11274-024-04174-w | |
4. | Lateef Babatunde Salam, Oluwafemi S. Obayori, Matthew O. Ilori, Olukayode O. Amund, Chromium contamination accentuates changes in the microbiome and heavy metal resistome of a tropical agricultural soil, 2023, 39, 0959-3993, 10.1007/s11274-023-03681-6 | |
5. | Oluwafemi Sunday Obayori, Lateef Babatunde Salam, Ahmeed Olalekan Ashade, Titilayo Damilola Oseni, Mandy Divine Kalu, Fareedah Mojisola Mustapha, An animal charcoal contaminated cottage industry soil highlighted by halophilic archaea dominance and decimation of bacteria, 2024, 40, 0959-3993, 10.1007/s11274-024-04136-2 | |
6. | Duguma Dibbisa, Tadesse Daba, Seid Mohammed, Regulatory Element Analysis and Comparative Genomics Study of Heavy Metal-Resistant Genes in the Complete Genome of Cupriavidus gilardii CR3, 2024, 18, 1177-9322, 10.1177/11779322241299905 | |
7. | Xiaofang Li, Bikram Basak, Rahul S. Tanpure, Xin Zheng, Byong-Hun Jeon, Unraveling the genetic basis of microbial metal resistance: Shift from mendelian to systems biology, 2025, 493, 03043894, 138350, 10.1016/j.jhazmat.2025.138350 |
Heavy metals | Genes | Functions of the proteins |
Lead | cadC | Cadmium efflux system accessory protein Function: Regulates the CadA gene involved in Pb, Cd, and Bi resistance. |
zntA | Lead, cadmium, zinc, and mercury transporting ATPase; Copper-translocating P-type ATPase Function: Activates to response stress signal in bacteria |
|
Arsenic | arsR | Arsenical resistance operon repressor |
arsC | Arsenate reductase thioredoxin-coupled, Low molecular weight phosphatases (LMWP) family | |
acr3 | Arsenical-resistance protein ACR3 | |
Cobalt | czcD | Cobalt/zinc/cadmium resistance protein CzcD |
Chromium | chrA | Chromate transport protein |
Heavy metals | Genes | Functions of the proteins |
Lead | cadC | Cadmium efflux system accessory protein Function: Regulates the CadA gene involved in Pb, Cd, and Bi resistance. |
zntA | Lead, cadmium, zinc, and mercury transporting ATPase; Copper-translocating P-type ATPase Function: Activates to response stress signal in bacteria |
|
Arsenic | arsR | Arsenical resistance operon repressor |
arsC | Arsenate reductase thioredoxin-coupled, Low molecular weight phosphatases (LMWP) family | |
acr3 | Arsenical-resistance protein ACR3 | |
Cobalt | czcD | Cobalt/zinc/cadmium resistance protein CzcD |
Chromium | chrA | Chromate transport protein |