Comparative genome and protein analysis for Acidithiobacillus ferrooxidans strains in terms of heavy metal binding as an application for biomining

Comparative genome and protein analysis for Acidithiobacillus ferrooxidans strains in terms of heavy metal binding as an application for biomining | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative genome and protein analysis for Acidithiobacillus ferrooxidans strains in terms of heavy metal binding as an application for biomining Bekele Oljira Negero This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7982109/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The majority of microorganisms cannot endure extreme conditions, including heavy metals, high salinity, acidity, alkalinity, and various stress factors. However, only a few can endure extreme environments, with the genus Acidithiobacillus being widely recognized. Studies have been conducted to demonstrate how proteomic alterations occur in reaction to heavy metals like copper, zinc, nickel, cadmium, potassium, iron, molybdenum, and arsenic. Entire genome sequencing of various Acidithiobacillus species has revealed new understandings of their roles. Four distinct functional gene categories were thoroughly examined for their capacity to bind heavy metals in the context of biomining applications. The complete genome sequence acquired was annotated and examined with Ezbiocloud software. Subsequently, utilizing the 16S rRNA gene sequence of the A. ferrooxidans YNTRS-40 strain, the sequence's purity was evaluated through cont16s rRNA provided by EZbiocloud. Based on the phylogeny derived, two extremes were noted: one being the nearest strain, A. ferrooxidans ATCC 23720 , and the other being the outgroup, A. albertensis DSM 14366. Twenty-two distinct heavy metal binding genes were examined using RAST annotation software. The genes included were Mod, ZnuA, ZnuC, MerP, SufA, PstB, PstS, PhnK, PhnL, FeoB, MntH, MerC, MgtC , and PhoU . The analyzed bacteria with these genes were recognized as having the potential for application in heavy metal bioremediation. Biotechnology and Bioengineering A.ferrooxidans biomining heavy metal binding genes Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Biomining is the method of extracting metals from ores and other solid substances, usually employing prokaryotes, fungi, or plants [ 1 ]. These organisms produce various organic compounds that bind metals from the surroundings and transport them back to the cell, where they are generally utilized to coordinate electrons. Among these microorganisms, Acidithiobacillus ferrooxidans stands out as a potential candidate [ 2 ]. The majority of microorganisms do not endure extreme conditions such as heavy metals, salinity, acidity, alkalinity, and stress. Nevertheless, certain microorganisms can endure in these harsh conditions, one of which is the Acidithiobacillus genus of bacteria. It has been stated that Acidithiobacillus plays a crucial role in the cycling of nutrients related to metals in the environment and can help in cleaning up metal-polluted sites by oxidizing and reducing these metals [ 3 , 4 ]. The Acidithiobacillus genus includes approximately nine recognized species such as A. ferrooxidans, A. albertensis, A. ferridurans, A. ferriphilus, A. ferrivorans, A. sulfuriphilus, and A. thiooxidans. Among these genera, A. ferrooxidans is the dominant one, featuring various species such as A. ferrooxidans NTRS-40 and A. ferrooxidans ATCC 23720. From A. ferridurans, A.ferridurans ATCC33020 is the recognized variant. A. ferrivorans NO-37 is a common variant of A. ferrivorans. A.ferrianus MG and A.ferriphilus M20 are likewise the species present in the Acidithibacillus genus of A.ferriansus and A.ferriphilus . Among these, the most researched microorganisms is A. ferrooxidans due to its capabilities to oxidize iron and sulfur, possible environmental adaptability, and extensive applications [ 4 , 5 ]. Acidithiobacillus ferrooxidans is a gram-negative, aerobic chemolithoautotrophic bacterium that thrives in acidic conditions. It acquires the energy needed for growth through the aerobic oxidation of Fe + 2 (ferrous iron) and H 2 S (reduced sulfur) compounds into Fe + 3 (ferric iron) and H 2 SO 4 (sulfuric acid), correspondingly. It can additionally utilize hydrogen or formate when Oxygen is present. Moreover, under anaerobic conditions [ 2 , 6 ], it can reduce ferric iron using sulfur or hydrogen as electron donors. It possesses distinctive metabolic functions. This resulted in it being one of the key bacteria for leaching heavy metals such as gold, copper, uranium, and cobalt from sulfide ores [ 3 , 7 ]. The unusual energetic metabolism of A. ferrooxidans is crucial to comprehend its bioleaching potential [ 3 , 8 ]. It is challenging to research A. ferrooxidans genetically. As a result, several proteomics and genomes investigations of A. ferrooxidans have been conducted in an effort to learn more about the processes underlying adaptability to environmental changes. Research has been done to find out how heavy metals like copper, zinc, nickel, cadmium, potassium, iron, molybdenum, arsenic, and others affect the proteome. A comparative proteomic and genomic approach was used to compare different species of A. ferrooxidans in order to gain insight into how the bacterium can withstand damage from heavy metals and how it binds to metals to oxidize or reduce [ 16 , 9 ]. In A. ferrooxidans , researchers have described a number of respiratory chain models, most notably iron-based energy metabolism. These theories were widely accepted and included the rus operon that encodes two c-type cytochromes, Cyc1 and Cyc2, an aa3-type cytochrome oxidase, rusticyanin, and an open reading frame (ORF) of unknown function. Results on the Sulphur respiratory chains have only recently been reported due to the complexity of the energetic metabolism of reduced Sulphur compounds [ 2 , 3 , 10 , 18 ]. New information on the roles of several Acidithiobacilli species has been made possible by whole genome sequencing. A. ferrooxidans YQH-1's complete genome sequencing has shown a large number of genes linked to carbon dioxide and dinitrogen fixation, pH tolerance, oxidative stress, heavy metal binding, and heavy metal detoxification [ 5 , 11 ]. Another work used whole-genome sequencing analysis and a bioinformatics technique to show sulphur oxidation in the extremophile Acidithiobacillus thiooxidans. Different researchers have employed transcriptional analysis to investigate the substrate regulation and gene identification of psychrotolerant Acidithiobacillus ferrivorans throughout a bioleaching process, allowing functional predictions made by genome analysis to be further evaluated by experimental methods. Little is known about the minerals created during the bioleaching process, despite the fact that metabolic routes for iron oxidation have been thoroughly investigated [ 1 , 5 , 12 ]. The comparative genome and proteome analysis of the A. ferrooxidan strain in terms of heavy metal binding has been addressed in this study. The whole genome sequence and annotation of A. ferrooxidan were used for this activity, and bioinformatics analyses of the genome of A. ferrooxidan allowed for the identification of numerous candidate genes related to heavy metal binding as a biomining application. Several of these putative genes were characterized in the present study by measuring their transcriptional expression profiles and functionality [ 16 , 18 ]. The remaining parts of the paper is organized as follows. In section 2 materials and methods is presented. Section 3 contains results and discussion of the study. Finally conclusion is drawn in Section 4. 2. Materials and Methods 2.1. Genome Overview The whole genome sequence obtained was annotated and analyzed using Ezbiocloud software. Next, using the A. ferrooxidan YNTRS-40 strain's 16S rRNA gene sequence, the purity of the sequence was analyzed by cont16s rRNA from EZbiocloud. Then two fragmented sequence obtained. One of the fragmented sequences was run blastn using NCBI Blastn software online. Then the top seven hits (100% similarity) were obtained and used for phylogenetic tree construction [ 3 , 15 , 20 , 21 ]. 2.2. Phylogenetic Tree Construction Using the top seven best hits of blastn results (100% similarity), phylogenetic tree was constructed using MEGA 11 software. MEGA11 software (CLUSTALW) was used to perform multiple alignment phylogenetic tree construction using likely hood method. Sequence alignment and average nucleotide identity (ANI) was analyzed using OnthoANI (OAT) software [ 6 , 7 , 20 , 21 ]. 2.3. Functional Gene Analysis The functional genes analysis was done using Rapid annotation using subsystem technology (RAST). To assign functions to the genes, predict subsystem in the genome and to predict metabolic functions of the assigned genes, Rapid Annotations using Subsystems Technology (RAST) was used. So, in this study RAST was used to analyze functional genes for heavy metal binding as an application for biomining. The RAST uses FIG FAM protein family subset to predict gene functions. Then functional genes used for heavy metal binding as an application for biomining. Finally the new strain formed would be described and housekeeping gene was identified [ 8 , 22 ]. 3. Results and Discussion 3.1. Results 3.1.1. Genome overview. With known genome assembly and base pairs arranged into two contigs (Table 1 ), the genome of the investigated Acidithiobacillus ferrooxidans YNTRS-40 strain was examined to look into its traits and activities [ 6 , 19 , 20 , 21 ]. When the genome was compared to other known Acidithiobacillus ferrooxidans genomes, the OrthoANI value for Acidithiobacillus ferrooxidans ATCC 23720 was 100%, while the OrthoANI value for A. albertensis DSM 14366 was at least 97.72% (Fig. 2 ). The substantial genetic variability in the A. ferrooxidans YNTRS-40 genome, which may be the consequence of long-term horizontal gene transfer or adaptation to severe environmental circumstances like pH stress, is probably the cause of the comparatively low pairwise nucleotide identity seen [ 6 , 20 , 21 ]. Table 1 Genomic information of A.ferrooxidans strain YNTRS-40 S/N Bacteria Genome size G + C CDS Contigs rRNA tRNA Gene size Ref 1 A.ferrooxidan YNTRS 40 3,257,037 58.5% 3,283 2 6 46 3,339 [ 6 ] 3.1.2. Analysis of 16S rRNA Gene For the bacterium under investigation ( A. ferrooxidans NTRS-40 ), accession number NZ_CP040511.1, the 16S rRNA gene sequence was acquired. With similarity values of 100%, a comparison of this sequence with closely related strains that were deposited in public databases verified that the strain A. ferrooxidans ATCC 23720 was associated with the species being studied. A. albertensis DSM 14366 had the lowest similarity of any strain in the database, at 97.72%, which was below the threshold level to be classified as belonging to the species [ 20 , 22 ]. All other strains in the database had similarities that were lower than this. So, based on the 16S rRNA gene, the phylogenetic position of A.albertensis DSM 14366 shown in Fig. 1 , is separated in an independent branch (outgroup) [ 6 , 17 ]. 3.1.3. Phylogenetic Construction Whole genome sequence was annotated using RAST (Rapid Annotation subsystem technology). For the construction of phylogenetic tree, first 16S rRNA gene sequence of A. ferrooxidan YNTRS-40 strain was fragmented by using database cont16S rRNA from Ezbiocloud. Then the obtained result was run blastn and finally phylogenetic tree was constructed by MEGA11 software using CLUSTAL W to perform a multiple alignments. The neighbor-joining method was used to construct a phylogenetic tree. During the construction of phylogenetic tree, Bootstrap values were calculated by MEGA 11 using likely hood method. Sequence alignment (SA) and Average Nucleotide Identity (ANI) analysis was performed using OAT software [ 20 , 21 , 22 ]. Genome annotations of bacteria under study revealed [ 24 ] the presence of various genes for iron (Fe) and sulfur (S) metabolism. In addition to this, aromatic compound degradation, stress response and metal resistance genes obtained (Table 4 ). 3.1.4. Genomic Nucleotide Analysis (Gene Ontology) (ANI) The gene ontology and genomic nucleotide analysis (ANI) showed the presence of different features compared with other available strains obtained from NCBI [ 20 , 22 ]. Table 2 General features of A.ferrooxidans NTRS-40 genome used in this study including six strains available on NCBI strain Genome size (bp) G + C Contigs CDSs rRNA tRNA Hit% A.fxdn NTRS-40 3,257,037 58.5% 2 3,283 6 46 100 A. fxdn ATCC 23270 2,982,397 58.8 1 3,042 6 78 100 A.frvorns No-37 3,207,552 56.6 1 3,250 6 47 100 A.fdur ATCC33020 2,921,399 58.4 1 3,033 6 46 100 A.ferriphilus M20 2,667,881 58.4 127 2,641 6 46 100 A. ferrianus MG 316,586 58.2 90 3,083 7 47 100 A. al DSM 14366 3,503,318 52.5 141 3,596 6 48 100 After the analysis of 16S rRNA gene sequence using EZBiocloud software, different categories of clustered strains of the bacterium has been seen [19. 20]. These were A. ferriphilus M20 , A. ferrivoransNO-37 , A. ferridurans ATCC33020 , A. ferrooxidans ATCC 23270 , A. ferriansus MG and A. albertensis DSM 14366 . This result was similar to a study done by [ 19 , 25 ]. ANI analysis showed that there is strong similarity between the strain under study and Acidithiobacillus ferrooxidans ATCC 23720 (Fig. 2 and Table 3 ) [ 20 ]. Figure 2 shows a heatmap and dendrogram illustrating the genetic clustering of Acidithiobacillus strains, highlighting their similarity levels and diversity, aiding in microbiology and evolutionary biology research. Table 3 Average nucleotide identity Analysis of Acidithiobacillus STRAIN MG DSM 14366 M20 NO-37 ATCC 23270 YNTRS 40 ATCC 33020 A. ferrianus MG A. albertensis dsm 14366 97.71 A. ferriphilus m20 98.47 97.19 A. ferrivorans no-37 98.03 97.23 99.09 A. ferrooxidans atcc 23270 97.85 97.59 98.23 97.76 A. ferrooxidans yntrs 40 97.93 97.72 98.18 97.84 100 A. ferridurans atcc 33020 98.49 97.72 99.01 98.2 98.71 98.7 3.1.5. Genomic analysis of Heavy metal binding, transport and resistance genes. The genome of Acidithiobacillus ferrooxidans NTRS-40 revealed different genes related to heavy metal binding and responsible for utilization as energy source. Sometimes these genes were lead in the activity of biomining as a result of bioremediation of heavy metals and toxic elements. During the analysis different heavy metal binding genes were identified using RAST software [ 16 , 23 , 24 ]. Among the genes analysed using the software, some of them are listed (Table 4 ). Up on the analysis 22 genes of heavy metal or element binding genes or proteins were identified as in bacteria under study. Out of these, 5 of them have no specific genes, only binding proteins were identified. They were 3 4Fe-4S ferredoxin, iron-sulfur binding proteins and 2 heavy metal binding proteins. From the identified genes, 3 genes were Molybdenum binding (ModC and 2Mod A), 2 Zinc binding (ZnuA and ZnuC), 7 Iron binding (TonB, 2HesB_2IscA_2SufA), 1 Mercury binding (MerP), and 4 Phosphate binding genes (PstB, PstS, PhnK and PhnL) (Table 4 and Fig. 3 ) [ 18 , 24 ]. Large number of genes responsible for resistance to toxic compounds and heavy metals were identified using genome analysis of the bacterium (Table 4 ). A number of genes important in heavy metal resistance and binding were observed in the membrane transport (ABC transporter system) and periplasmic membrane (Fig. 3 ) [ 16 , 17 ]. Heavy metal transport system proteins and genes analysed from the bacterium under study was Iron and ferric transport genes and proteins ( TonB, FeoB and TonB -dependent receptor), magnesium and cobalt transport protein ( CorA ), Managanese transport protein ( MntH ), Mercuric transport protein ( MerC ), Mg(2+)-transport-ATPase-associated protein (MgtC ), molybdenum ABC transporter ATP-binding protein (ModC ), molybdenum ABC transporter, substrate-binding protein ( ModA ), molybdenum transport system protein ( ModD ), phosphate ABC transporter, ATP-binding protein ( PstB ), phosphate ABC transporter, permease protein ( PstA ), phosphate ABC transporter, permease protein (PstC ), phosphate ABC transporter, substrate-binding protein (PstS ), phosphate transport system regulatory protein ( PhoU ), phospholipid ABC transporter shuttle protein ( MlaC ), potassium-transporting ATPase A chain (EC 3.6.3.12) (TC 3.A.3.7.1), potassium-transporting ATPase B chain (EC 3.6.3.12) (TC 3.A.3.7.1), potassium-transporting ATPase C chain (EC 3.6.3.12) (TC 3.A.3.7.1), sodium-transporting ATPase subunit G, zinc ABC transporter, ATP-binding protein ( ZnuC ), zinc ABC transporter, permease protein ( ZnuB ), zinc ABC transporter, substrate-binding protein ( ZnuA ) and Copper-translocating P-type ATPase EC 3.6.3.4 for transporting lead, cadmium, zinc and mercury [ 17 , 24 ]. In addition to heavy metal transport system, there were heavy metal resistance genes and proteins analyzed from genome of the A.ferrooxidans NTRS-40 bacterium like Arsenic resistance protein ( ArsH ), Cobalt/zinc/cadmium resistance protein ( CzcD ), Cobalt-zinc-cadmium resistance protein, Copper resistance protein ( CopC ), Copper resistance protein ( CopD ) and Mercuric resistance operon regulatory protein ( MerR ) [ 16 , 18 , 24 ]. Table 4 Lists of genes and proteins involved in heavy metals and elements binding Analysis of Acidithiobacillus ferrooxidans NTRS-40 Heavy metal and element binding genes and proteins Gene Proteins ModC Molybdenum-binding protein ModA Molybdenum ABC, periplasmic molybdenum-binding protein ZnuA Zinc ABC, periplasmic-binding protein ZnuC Zinc ABC, ATP-binding protein IscA Iron binding protein for iron-sulfur cluster assembly TonB Ferric siderophore, periplasmic binding protein HesB_IscA_SufA probable iron binding protein HesB_IscA_SufA probable iron binding protein in Nif operon MerP Periplasmic mercury(+ 2) binding protein PstB Phosphate-binding protein PstS Phosphate ABC, periplasmic phosphate-binding protein PhnK, PhnL Phosphonates-binding protein Table 4 shows different genes and the proteins they produce, which are involved in binding and transporting various essential elements and heavy metals across the cell membrane. These proteins play important roles in cellular processes and help the cell adapt to different environmental conditions. Each gene is associated with a specific protein and its function, such as binding molybdenum, zinc, iron, and mercury, phosphate, and phosphonate compounds for transport or utilization within the cell [ 17 , 18 ]. The chromosomal region of the focus gene (top) is compared with similar organisms. The graph is centered on the focus gene, which is red and numbered and denoted 1. Sets of genes with similar sequence are grouped with the same number and color. Genes whose relative position is conserved in at least four other species are functionally coupled and share gray background boxes. As it was shown by Rasta viewer software, focus gene always points to the right (Figs. 3 and 4 ) [ 24 ]. Table 5 Heavy metal transporter and binding proteins and their associated gene heavy metal transporter and binding proteins and their associated gene Genes Proteins TonB Ferric siderophore transport system, periplasmic binding protein FeoB Ferrous iron transporter CorA Magnesium and cobalt transport protein MntH Manganese transport protein MerC Mercuric transport protein, MgtC Mg(2+)-transport-ATPase-associated protein ModC Molybdenum ABC transporter ATP-binding protein ModA Molybdenum ABC transporter, substrate-binding protein ModD Molybdenum transport system protein PstB Phosphate ABC transporter, ATP-binding protein PstA, PstC Phosphate ABC transporter, permease protein PstS Phosphate ABC transporter, substrate-binding protein PhoU Phosphate transport system regulatory protein MlaC Phospholipid ABC transporter shuttle protein ZnuC Zinc ABC transporter, ATP-binding protein ZnuB Zinc ABC transporter, permease protein ZnuA Zinc ABC transporter, substrate-binding protein Not Identified ABC-type Fe3+-siderophore transport system permease component Not Identified Heavy metal transport/detoxification protein Not Identified Lead, cadmium, zinc and mercury transporting ATPase (EC 3.6.3.3) (EC 3.6.3.5); Copper-translocating P-type ATPase (EC 3.6.3.4) Not Identified Potassium-transporting ATPase A chain (EC 3.6.3.12) (TC 3.A.3.7.1) Not Identified Sodium-transporting ATPase subunit G Table 5 indicates various genes and the proteins they produce, which are involved in transporting essential elements and heavy metals across bacterial membranes which were summarized from RAST viewer [ 24 ]. These proteins play crucial roles in the uptake, transport, and detoxification of substances like iron, magnesium, cobalt, manganese, mercury, molybdenum, phosphate, phospholipids, and zinc. They also contribute to the adaptation and survival of bacteria in different environments. Each gene is associated with a specific protein and its function, such as transporting specific ions or molecules across the bacterial membrane. Table 6 Heavy metal Resistance genes and associated proteins Heavy metal Resistance genes and associated proteins Genes associated proteins ArsH , Arsenic resistance protein CzcD , Cobalt/zinc/cadmium resistance protein CzcD Cobalt/zinc/cadmium resistance protein CopC Copper resistance protein CopD Copper resistance protein MerR , Mercuric resistance operon regulatory protein Table 6 describes genes and the proteins they produce, which are involved in heavy metal resistance. These proteins play crucial roles in protecting organisms from the toxic effects of these heavy metals, allowing them to survive and adapt in environments with high metal levels. Each gene is associated with a specific protein that helps the organism resist a particular heavy metal, and their functions are essential for the adaptation and survival of the organisms in challenging conditions. 3.2. Discussion The A.ferrooxidans NTRS-40’s genome was analysed using different software like EZBiocloud, CLASTAL W, OAT, MEGA 11 and others. The result has confirmed the presence of arrangement of genes and proteins involved in heavy metal resistance. Some of them were metal-binding proteins, metal transporters, metal chelators, metal reductases, and metal-resistant genes. In addition, there were also genes and proteins capable of binding, transporting, reducing and oxidizing for the survival and resistance of the bacteria, which is in the same result with [ 9 , 23 ]. For the average nucleotide identity or ortho OAT ANI analysis and phylogenetic characterization of the Bacterium of the study, the results indicated a relationship with the A.ferrooxidans ATCC 23720. 16S rRNA gene phylogeny was studied to evaluate the taxonomic position of the bacterium under study within other members, showing a close relationship with A. ferridurans (98.18%), A. pherriphilus (98.18%), A. ferrianus (97.93%), A. ferrivorans (97.54%) and A. albertensis (97.73). This phylogenetic tree showed that A.ferrooxidans ATCC 23720 has 100% similarity with bacterium under study. This showed both bacteria were categorized in the same species. But A. albertensis DSM 14366 showed the least similarity with A.ferrooxidans NTRS-40 . But according to [ 10 , 21 , 23 ], bacterial strain A.albertensis DSM 142366 is not outgrouped from the branch. According to the phylogenetic tree, this bacterium was found in outgroup branch of the phylogeny. The bacterium A.ferrooxidans NTRS-40 was branched together with A.ferrooxidans ATCC 23720 with the highest value (100%), indicating it was closely related to the A.ferrooxidans NTRS-40 .They also categorized under the same species when other bacterial groups in this study were in different species. In response to heavy metals resistance, the bacterium has developed different genetic mechanisms like heavy metals binding proteins and genes, heavy metals transporting proteins and genes and also heavy metals resistance genes and proteins. This was showed the bacterium can grow and remediate the toxified soils and other environments [ 11 ]. A.ferridurans ATCC33020 was also reported to have tolerance to heavy metals and capable to remediate the soils as well as environments [ 11 , 12 , 13 ]. When bacterial groups associated with bacteria under study ( A.ferrooxidans NTRS-40 ) in the phylogenetic tree and Ortho ANI were compared, only A. ferroxidans ATCC 23720 strain was related with functional genes during functional gene analysis by RAST software [ 23 ]. When compared between the two strains with functional gene analysis, A.ferrooxidans NTRS-40 had more functional genes of heavy metal resistance and binding genes. So, from comparative analysis, these bacterial strains ( A. ferrooxidans NTRS-40 and A.ferrooxidans ATCC 23720 ) are highly involved in biomining and heavy metal binding. This indicated that they play a great role in biomining of heavy metals as heavy metal bioremediation activity. This is supported by [ 14 ] the two strains have similar functional genes ZunC and PstB which involves in binding of Zink and Phosphate compound. In previous study, it was known that the bacterium under study has increased levels of proteins. These proteins were related to LPS synthesis which could be of great importance for heavy metal resistance. Due to this, various microorganism like Pseudomonas aeruginosa can accumulate metals on the cell surface through electrostatic interactions with LPS present in its membrane [ 1 , 15 ]. Tables 4 , 5 and 6 describes different genes and the proteins they produce, which are involved in binding and transporting essential elements and heavy metals across cell membranes, bacterial membranes, and providing resistance to heavy metals. These proteins play vital roles in cellular processes, bacterial adaptation, and protecting organisms from the toxic effects of heavy metals, enabling survival in challenging environments. Each gene is associated with a specific protein and function, such as binding, transporting, or providing resistance to particular ions or molecules, essential for cellular and bacterial survival and adaptation. 4. Conclusions Genomic and functional analysis of A. ferrooxidans ATCC NTRS-40 revealed that they are highly capable of avoiding the toxicity of heavy metals in their surroundings. The majority of the heavy metal-exposed proteins in A. ferrooxidans NTRS-40 are linked to other bacterial strains, especially A. ferrooxidans ATCC 23720 . Given the challenges in doing conventional genetic research on this microbe, bioinformatics analysis of the entire genome of A. ferrooxidans NTRS-40 offers a useful tool for gene identification and functional gene prediction. A comprehensive understanding of this bacterial gene composition, transport systems, heavy metal resistance, heavy metal binding, and metabolic capacity can be obtained by a genome study. These cellular functions underpin the essential traits of A. ferrooxidans that relate to its application in commercial biomining, such as its capacity to oxidize iron and sulphur, withstand low pH, and survive in settings that contain potentially hazardous organic and inorganic substances. Additionally, they imply that it can move metals from the cell to the surroundings, which would help the bioleaching of copper, zinc, mercury, molybdenum, cobalt, and other heavy metals. Additionally, the research generated a number of predictions that may prove helpful in understanding biomining systems. Finally, the study reviewed that A.ferrooxidans ATCC 23720 is the most closely related strain to the bacterium under study, with 100% similarity in average nucleotide identity (ANI). Additionally, further researches will be important to analyze the practical application of these identified functional genes in heavy metal binding, transporting and resisting heavy metals in different areas, such as industries. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials Not applicable. Competing interests The authors declare that they have no competing interests. Funding There was no funding support for this research. Authors' contributions The submitted version of the paper was approved by all authors who contributed equally. Acknowledgements Not applicable. References Ramos-Zúñiga J, Gallardo Sebastián, Martínez-Bussenius Cristóbal, Norambuena R, Navarro CA, Paradela A, Jerez CA (2018) Response of the biomining Acidithiobacillus ferrooxidans to high cadmium concentrations. J Proteom. https://doi.org/10.1016/j.jprot.12.013 Luo H, Shen L, Yin H, Li Q, Chen Q, Luo Y, Liao L, Qiu G (2009) and X. Liu. Comparative genomic analysis of Acidithiobacillus ferrooxidans strains using the A. ferrooxidans ATCC 23270 whole-genome oligonucleotide microarray School of Minerals Processing and Bioengineering, Central South University, Changsha, Hunan 410083, China Zhang X, She S, Dong W, Niu J, Liang YXY, Liu X, Zhang X, Fan F (2016) Huaqun Yin. Comparative genomics unravels metabolic differences at the speciesand/or strain level and extremely acidic environmental adaptation often bacteria belonging to the genus Acidithiobacillus. http://dx.doi.org/10.1016/j.syapm.2016.08.007 Tran TTT, Mangenot S, Magdelenat G, Payen E, Rouy Z, Belahbib H, Grail BM, Johnson DB, Bonnefoy V, Talla E (2017) Comparative Genome Analysis Provides Insights into Both the Lifestyle of Acidithiobacillus ferrivorans Strain CF27 and the Chimeric Nature of the Iron-Oxidizing Acidithiobacilli Genomes. Front Microbiol 8:1009. 10.3389/fmicb.2017.01009 Anila Fariq JC, Blazier A, Yasmin, Terry J (2019) Gentry & Youjun Deng. Whole genome sequence analysis reveals high genetic variation of newly isolated Acidithiobacillus ferrooxidans IO. https://doi.org/10.1038/s41598-019-49213-x . -2C Zhang Y, Zhang S, Zhao D, Ni Y, Wang W Lei Yan. Complete genome sequence of Acidithiobacillus ferrooxidans YNTRS-40, a strain of the ferrous iron and sulfur-oxidizing acidophile 2019, https://doi.org/10.21203/rs.2.17384/v1 Zhang X, Liu Z, Wei G, Yang F, Liu X In Silico Genome-Wide Analysis Reveals the Potential Links Between Core Genome of Acidithiobacillus thiooxidans and Its Autotrophic Lifestyle. Front Microbiol 2018 9:1255. 10.3389/fmicb.2018.01255 Kapilesh Jadhav · Bijayendra Kushwaha (2021) · Indrani Jadhav · Prem Shankar · Anjali Geethadevi · Gaurav Kumar ·Sonam Mittal · Guru Prasad Sharma · Madhuri Parashar,· Deepak Parashar, Genomic analysis of a novel species Halomonas shambharensis isolated from hypersaline lake in Northwest India. https://doi.org/10.1007/s11033-020-06131 Jorge Valdés I, Pedroso R, Quatrini RJ, Dodson H, Tettelin R, Blake II, Jonathan A, Eisen, David S, Holmes (2008) Acidithiobacillus ferrooxidans metabolism : from genome sequence to industrial applications. http://creativecommons.org/licenses/by/2.0 Jiri Kucera O, Sedo D, Potesil O, Janiczek Z, Zdrahal M, Mandl (2016) Comparative proteomic analysis of sulfur-oxidizing Acidithiobacillus ferrooxidans CCM 4253 cultures having lost the ability to couple anaerobic elemental sulfur oxidation with ferric iron reduction. Res Microbiol. http://dx.doi.org/10.1016/ Chen J, Liu Y, Diep P, Mahadevan R (2021) Genomic Analysis of a Newly Isolated Acidithiobacillus ferridurans JAGS Strain Reveals Its Adaptation to Acid Mine Drainage. Minerals 11:74. https://doi.org/10.3390/min11010074 Harold Nu ~ nez PC, Covarrubias A, Moya-Beltr!an F, Issotta LG, Acu ~ na DB, Johnson (2016) Raquel Quatrini. Detection, identification and typing of Acidithiobacillus species and strains:a review. http://dx.doi.org/10.1016/j.resmic.2016.05.006 Dan Zhao · Jian Yang · Tao Liu · Dong Lu · Shuang Zhang · Lei Yan · Yongqing Ni. Complete Genome Sequence Analysis of Acidithiobacillus ferrivorans XJFY6S-08 Reveals Environmental Adaptation to Alpine Acid Mine Drainage. (2021) https://doi.org/10.1007/s00284-021-02423-x Linda Dekker F, Arsene-Ploetze JM, Santini (2015) Comparative proteomics of Acidithiobacillus ferrooxidans grown in the presence and absence of uranium. http://dx.doi.org/10.1016/j.resmic.2016.01.007 Rui Liu L, Ma H, Wang D, Liu X, Lu X, Huang (2023) Shanshan Huang and Xueduan Liu. Comparative genomics reveals intraspecific divergence of Acidithiobacillus ferrooxidans : insights from evolutionary adaptation. 10.1099/mgen.0.001038 Zhang S (2018) · Lei Yan · Weijia Xing · Peng Chen · Yu Zhang · Weidong Wang. Acidithiobacillus ferrooxidans and its potential application. https://doi.org/10.1007/s00792-018-1024-9 Anjana, Pandey (2011) Anand Srivastava and Ashutosh Pandey. Acidithiobacillus ferrooxidans : A bioleaching bacteria for better iron (II) oxidation ability. Int J Innovations Biol Chem Sci 1:32–37 Carro L, Veyisoglu A, Guven K, Schumann P, Klenk H-P, Sahin N (2022) Genomic Analysis of a Novel Heavy Metal Resistant Isolate from a Black Sea Contaminated Sediment with the Potential to Degrade Alkanes: Plantactinospora alkalitolerans sp. nov. Diversity 14:947. https://doi.org/10.3390/d14110947 Yue Zhan · Mengran Yang · Shuang Zhang · Dan Zhao · Jiangong Duan · Weidong Wang · Lei Yan. Iron and sulfur oxidation pathways of Acidithiobacillus ferrooxidans. (2019). https://doi.org/10.1007/s11274-019-2632-y Yoon S, Ha S, Lim J, Kwon S, Chun J (2017) A large-scale evaluation of algorithms to calculate average nucleotide identity. Antonie Van Leeuwenhoek 110(10):1281–1286. https://doi.org/10.1007/s10482-017-0844-4 Lee I, Chalita M, Ha S, Na S, Yoon S, Chun J (2017) ContEst16S: An algorithm that identifies contaminated prokaryotic genomes using 16S RNA gene sequences. Int J Syst Evol MicroBiol 67(6):2053–2057. https://doi.org/10.1099/ijsem.0.001872 Lee I, Kim O, Park Y, S., Chun J, OrthoANI (2016) An improved algorithm and software for calculating average nucleotide identity. Int J Syst Evol MicroBiol 66(2):1100–1103. https://doi.org/10.1099/ijsem.0.000760 Overbeek R (2005) The subsystems approach to genome annotation and its use in the project to annotate 1000 genomes. Nucleic Acids Res 33(17):5691–5702. https://doi.org/10.1093/nar/gki866 Rapid annotation using subsystem technology (RAST) https://rast.nmpdr.org/rast.cgi National Center for Biotechnology Information (NCBI) https://www.ncbi.nlm.nih.gov/ Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7982109","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":537045835,"identity":"71753131-42bb-4ca1-b551-3c13bc54956a","order_by":0,"name":"Bekele Oljira Negero","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEklEQVRIiWNgGAWjYBACAwY2BoYHQAYfw8EGBoYKqDAPIS0JQAYbWMsZqGoePNqQtAABYxsRWszZ2xIfJFQwyLExHm778HOenb29RALjg7dtDHL2OLRY9hw7bJBwhsEY6LDmmb3bkhN7JBKYDee2MRjjdNiN9DaJxDYGIDrYzMC7jTmBRyKBTZoXKNKDS8v95+0/Ev9BtDD+nVNvD9TC/huopR6nlhtsxxgSGyBamHkbDjMCHcbGDNSSgMthlj1pyRIJxyTAfmGWOXY8sefMw2bJOeckDHsO4AqxY4YfPtTYyPFLHH/M+Kam2p69PfnghzdlNvLsDTisgQAJIIIbytgAESEI+PEbOgpGwSgYBSMYAAC+j1RaWTvvgAAAAABJRU5ErkJggg==","orcid":"","institution":"Adama Science and Technology University","correspondingAuthor":true,"prefix":"","firstName":"Bekele","middleName":"Oljira","lastName":"Negero","suffix":""}],"badges":[],"createdAt":"2025-10-29 16:47:35","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-7982109/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7982109/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94734508,"identity":"7499fb75-cf2f-45d2-b80e-0d400701aeca","added_by":"auto","created_at":"2025-10-30 07:25:29","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":304063,"visible":true,"origin":"","legend":"","description":"","filename":"ComparativegenomeandproteinanalysisforAcidithiobacillusferrooxidans.docx","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/8afcdc23ea28b2e4fa9e7111.docx"},{"id":94734501,"identity":"dd99841e-a5f0-49d6-a5ea-c3150d45f0c5","added_by":"auto","created_at":"2025-10-30 07:25:29","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":342,"visible":true,"origin":"","legend":"","description":"","filename":"rs7982109.json","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/d77037e18ffaf40fc90dd6fb.json"},{"id":94734497,"identity":"cc0559a0-2b8f-4993-aef4-6b972ada9061","added_by":"auto","created_at":"2025-10-30 07:25:28","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":103337,"visible":true,"origin":"","legend":"","description":"","filename":"rs79821090enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/cfaa9121fba5e33c3caaffc3.xml"},{"id":94734504,"identity":"bc8227b7-c804-4e89-8365-13abed834051","added_by":"auto","created_at":"2025-10-30 07:25:29","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10715,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/174949dbe132c9a02c093d5c.png"},{"id":94734506,"identity":"9ce16809-42b4-47b8-bb60-08141023e9c2","added_by":"auto","created_at":"2025-10-30 07:25:29","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":55721,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/e2ea8640a1b74b2f72fc743b.png"},{"id":94823893,"identity":"d174698f-5d51-452c-a25b-dda032653754","added_by":"auto","created_at":"2025-10-31 06:48:15","extension":"jpeg","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":318857,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/1c09a84e49165f5c5b5f9e14.jpeg"},{"id":94823021,"identity":"73aca0aa-8f6f-425b-a726-feff3b047a88","added_by":"auto","created_at":"2025-10-31 06:45:51","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":114346,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/e0e2a57904e034aad488f702.png"},{"id":94823112,"identity":"10890e1e-8a4c-4e3b-b8a4-6583e23d82c2","added_by":"auto","created_at":"2025-10-31 06:46:10","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8550,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/8959c9c306c97aca013b4771.png"},{"id":94734503,"identity":"2401e2f4-af05-4379-ae76-ebdc525caa55","added_by":"auto","created_at":"2025-10-30 07:25:29","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":13143,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/c134bb626252816a7b5ac901.png"},{"id":94734500,"identity":"4595a732-1a0b-4df1-8381-050e9e9a9982","added_by":"auto","created_at":"2025-10-30 07:25:29","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":81348,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/057fb6011d7f4fed84dc31cf.png"},{"id":94734516,"identity":"545ad81f-5413-4bf9-a6df-41a7fdcda742","added_by":"auto","created_at":"2025-10-30 07:25:29","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":35593,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/f7b1f2c0fd195ea770dc6409.png"},{"id":94734513,"identity":"b6a8ac6b-2673-45a5-aed3-40346e4de75e","added_by":"auto","created_at":"2025-10-30 07:25:29","extension":"xml","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":102393,"visible":true,"origin":"","legend":"","description":"","filename":"rs79821090structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/db2919d1284b400262a94414.xml"},{"id":94734511,"identity":"b2c4b35b-4fe8-4d2b-a80b-877d2f3ffd5f","added_by":"auto","created_at":"2025-10-30 07:25:29","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":112417,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/c9e3f63726ad3f327a6d2579.html"},{"id":94734496,"identity":"8760dd05-becb-49d6-8fea-83f9f6b4f1ae","added_by":"auto","created_at":"2025-10-30 07:25:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":37842,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree of \u003cem\u003eA. ferrooxidansstrain YNTRS-40\u003c/em\u003e with reference strains obtained from database.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/a5223e3304f1b38ab9b3b5c1.png"},{"id":94734499,"identity":"df65c5f5-3bf8-47be-b348-bbf7fb94d076","added_by":"auto","created_at":"2025-10-30 07:25:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38056,"visible":true,"origin":"","legend":"\u003cp\u003eGene Onthology of \u003cem\u003eA. ferrooxidans\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/59172b93009286c4de7e0684.png"},{"id":94734507,"identity":"632b8f93-59da-4784-99c0-42135aca2c45","added_by":"auto","created_at":"2025-10-30 07:25:29","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":242215,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional gene annotation for Acidithiobacillus ferrooxidans with genes involved in heavy metal binding\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/27699e3fff2e6e05edb059f5.png"},{"id":94734512,"identity":"a53876e1-7232-4ec5-a01f-14ca36290caf","added_by":"auto","created_at":"2025-10-30 07:25:29","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":79476,"visible":true,"origin":"","legend":"\u003cp\u003eMolybdenum ABC transporter, substrate-binding protein ModA\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/54cfff825874422fc96219d0.png"},{"id":94827206,"identity":"20d730aa-a2d3-490f-acc9-1c8293ddfe22","added_by":"auto","created_at":"2025-10-31 06:55:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1379438,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7982109/v1/5f662b3c-ffd9-44db-9492-336e55db5b2a.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eComparative genome and protein analysis for Acidithiobacillus ferrooxidans strains in terms of heavy metal binding as an application for biomining\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eBiomining is the method of extracting metals from ores and other solid substances, usually employing prokaryotes, fungi, or plants [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These organisms produce various organic compounds that bind metals from the surroundings and transport them back to the cell, where they are generally utilized to coordinate electrons. Among these microorganisms, \u003cem\u003eAcidithiobacillus ferrooxidans\u003c/em\u003e stands out as a potential candidate [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The majority of microorganisms do not endure extreme conditions such as heavy metals, salinity, acidity, alkalinity, and stress. Nevertheless, certain microorganisms can endure in these harsh conditions, one of which is the \u003cem\u003eAcidithiobacillus\u003c/em\u003e genus of bacteria. It has been stated that \u003cem\u003eAcidithiobacillus\u003c/em\u003e plays a crucial role in the cycling of nutrients related to metals in the environment and can help in cleaning up metal-polluted sites by oxidizing and reducing these metals [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The \u003cem\u003eAcidithiobacillus\u003c/em\u003e genus includes approximately nine recognized species such as \u003cem\u003eA. ferrooxidans, A. albertensis, A. ferridurans, A. ferriphilus, A. ferrivorans, A. sulfuriphilus, and A. thiooxidans.\u003c/em\u003e Among these genera, \u003cem\u003eA. ferrooxidans\u003c/em\u003e is the dominant one, featuring various species such as \u003cem\u003eA. ferrooxidans NTRS-40\u003c/em\u003e and \u003cem\u003eA. ferrooxidans ATCC 23720.\u003c/em\u003e From \u003cem\u003eA. ferridurans, A.ferridurans ATCC33020\u003c/em\u003e is the recognized variant. \u003cem\u003eA. ferrivorans NO-37\u003c/em\u003e is a common variant of \u003cem\u003eA. ferrivorans. A.ferrianus MG\u003c/em\u003e and \u003cem\u003eA.ferriphilus M20\u003c/em\u003e are likewise the species present in the \u003cem\u003eAcidithibacillus\u003c/em\u003e genus of \u003cem\u003eA.ferriansus\u003c/em\u003e and \u003cem\u003eA.ferriphilus\u003c/em\u003e. Among these, the most researched microorganisms is \u003cem\u003eA. ferrooxidans\u003c/em\u003e due to its capabilities to oxidize iron and sulfur, possible environmental adaptability, and extensive applications [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cem\u003eAcidithiobacillus ferrooxidans\u003c/em\u003e is a gram-negative, aerobic chemolithoautotrophic bacterium that thrives in acidic conditions. It acquires the energy needed for growth through the aerobic oxidation of Fe\u003csup\u003e+\u0026thinsp;2\u003c/sup\u003e (ferrous iron) and H\u003csub\u003e2\u003c/sub\u003eS (reduced sulfur) compounds into Fe\u003csup\u003e+\u0026thinsp;3\u003c/sup\u003e (ferric iron) and H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e (sulfuric acid), correspondingly. It can additionally utilize hydrogen or formate when Oxygen is present. Moreover, under anaerobic conditions [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], it can reduce ferric iron using sulfur or hydrogen as electron donors. It possesses distinctive metabolic functions. This resulted in it being one of the key bacteria for leaching heavy metals such as gold, copper, uranium, and cobalt from sulfide ores [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The unusual energetic metabolism of \u003cem\u003eA. ferrooxidans\u003c/em\u003e is crucial to comprehend its bioleaching potential [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIt is challenging to research \u003cem\u003eA. ferrooxidans\u003c/em\u003e genetically. As a result, several proteomics and genomes investigations of \u003cem\u003eA. ferrooxidans\u003c/em\u003e have been conducted in an effort to learn more about the processes underlying adaptability to environmental changes. Research has been done to find out how heavy metals like copper, zinc, nickel, cadmium, potassium, iron, molybdenum, arsenic, and others affect the proteome. A comparative proteomic and genomic approach was used to compare different species of \u003cem\u003eA. ferrooxidans\u003c/em\u003e in order to gain insight into how the bacterium can withstand damage from heavy metals and how it binds to metals to oxidize or reduce [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn \u003cem\u003eA. ferrooxidans\u003c/em\u003e, researchers have described a number of respiratory chain models, most notably iron-based energy metabolism. These theories were widely accepted and included the rus operon that encodes two c-type cytochromes, Cyc1 and Cyc2, an aa3-type cytochrome oxidase, rusticyanin, and an open reading frame (ORF) of unknown function. Results on the Sulphur respiratory chains have only recently been reported due to the complexity of the energetic metabolism of reduced Sulphur compounds [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eNew information on the roles of several Acidithiobacilli species has been made possible by whole genome sequencing. \u003cem\u003eA. ferrooxidans YQH-1's\u003c/em\u003e complete genome sequencing has shown a large number of genes linked to carbon dioxide and dinitrogen fixation, pH tolerance, oxidative stress, heavy metal binding, and heavy metal detoxification [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Another work used whole-genome sequencing analysis and a bioinformatics technique to show sulphur oxidation in the extremophile Acidithiobacillus thiooxidans. Different researchers have employed transcriptional analysis to investigate the substrate regulation and gene identification of psychrotolerant \u003cem\u003eAcidithiobacillus ferrivorans\u003c/em\u003e throughout a bioleaching process, allowing functional predictions made by genome analysis to be further evaluated by experimental methods. Little is known about the minerals created during the bioleaching process, despite the fact that metabolic routes for iron oxidation have been thoroughly investigated [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe comparative genome and proteome analysis of the A. ferrooxidan strain in terms of heavy metal binding has been addressed in this study. The whole genome sequence and annotation of A. ferrooxidan were used for this activity, and bioinformatics analyses of the genome of A. ferrooxidan allowed for the identification of numerous candidate genes related to heavy metal binding as a biomining application. Several of these putative genes were characterized in the present study by measuring their transcriptional expression profiles and functionality [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe remaining parts of the paper is organized as follows. In section 2 materials and methods is presented. Section 3 contains results and discussion of the study. Finally conclusion is drawn in Section 4.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Genome Overview\u003c/h2\u003e\u003cp\u003eThe whole genome sequence obtained was annotated and analyzed using Ezbiocloud software. Next, using the \u003cem\u003eA. ferrooxidan YNTRS-40\u003c/em\u003e strain's 16S rRNA gene sequence, the purity of the sequence was analyzed by cont16s rRNA from EZbiocloud. Then two fragmented sequence obtained. One of the fragmented sequences was run blastn using NCBI Blastn software online. Then the top seven hits (100% similarity) were obtained and used for phylogenetic tree construction [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Phylogenetic Tree Construction\u003c/h2\u003e\u003cp\u003eUsing the top seven best hits of blastn results (100% similarity), phylogenetic tree was constructed using MEGA 11 software. MEGA11 software (CLUSTALW) was used to perform multiple alignment phylogenetic tree construction using likely hood method. Sequence alignment and average nucleotide identity (ANI) was analyzed using OnthoANI (OAT) software [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Functional Gene Analysis\u003c/h2\u003e\u003cp\u003eThe functional genes analysis was done using Rapid annotation using subsystem technology (RAST). To assign functions to the genes, predict subsystem in the genome and to predict metabolic functions of the assigned genes, Rapid Annotations using Subsystems Technology (RAST) was used. So, in this study RAST was used to analyze functional genes for heavy metal binding as an application for biomining. The RAST uses FIG FAM protein family subset to predict gene functions. Then functional genes used for heavy metal binding as an application for biomining. Finally the new strain formed would be described and housekeeping gene was identified [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Results\u003c/h2\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e3.1.1. Genome overview.\u003c/h2\u003e\u003cp\u003eWith known genome assembly and base pairs arranged into two contigs (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), the genome of the investigated \u003cem\u003eAcidithiobacillus ferrooxidans YNTRS-40\u003c/em\u003e strain was examined to look into its traits and activities [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. When the genome was compared to other known \u003cem\u003eAcidithiobacillus ferrooxidans\u003c/em\u003e genomes, the OrthoANI value for \u003cem\u003eAcidithiobacillus ferrooxidans ATCC 23720\u003c/em\u003e was 100%, while the OrthoANI value for \u003cem\u003eA. albertensis DSM 14366\u003c/em\u003e was at least 97.72% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The substantial genetic variability in the \u003cem\u003eA. ferrooxidans YNTRS-40\u003c/em\u003e genome, which may be the consequence of long-term horizontal gene transfer or adaptation to severe environmental circumstances like pH stress, is probably the cause of the comparatively low pairwise nucleotide identity seen [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGenomic information of A.ferrooxidans strain YNTRS-40\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS/N\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBacteria\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGenome size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eG\u0026thinsp;+\u0026thinsp;C\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCDS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eContigs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003erRNA\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003etRNA\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eGene size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA.ferrooxidan YNTRS 40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3,257,037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3,283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3,339\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e3.1.2. Analysis of 16S rRNA Gene\u003c/h2\u003e\u003cp\u003eFor the bacterium under investigation (\u003cem\u003eA. ferrooxidans NTRS-40\u003c/em\u003e), accession number NZ_CP040511.1, the 16S rRNA gene sequence was acquired. With similarity values of 100%, a comparison of this sequence with closely related strains that were deposited in public databases verified that the strain \u003cem\u003eA. ferrooxidans ATCC 23720\u003c/em\u003e was associated with the species being studied. \u003cem\u003eA. albertensis DSM 14366\u003c/em\u003e had the lowest similarity of any strain in the database, at 97.72%, which was below the threshold level to be classified as belonging to the species [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. All other strains in the database had similarities that were lower than this. So, based on the 16S rRNA gene, the phylogenetic position of \u003cem\u003eA.albertensis DSM 14366\u003c/em\u003e shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, is separated in an independent branch (outgroup) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e3.1.3. Phylogenetic Construction\u003c/h2\u003e\u003cp\u003eWhole genome sequence was annotated using RAST (Rapid Annotation subsystem technology). For the construction of phylogenetic tree, first 16S rRNA gene sequence of \u003cem\u003eA. ferrooxidan YNTRS-40\u003c/em\u003e strain was fragmented by using database cont16S rRNA from Ezbiocloud. Then the obtained result was run blastn and finally phylogenetic tree was constructed by MEGA11 software using CLUSTAL W to perform a multiple alignments. The neighbor-joining method was used to construct a phylogenetic tree. During the construction of phylogenetic tree, Bootstrap values were calculated by MEGA 11 using likely hood method. Sequence alignment (SA) and Average Nucleotide Identity (ANI) analysis was performed using OAT software [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Genome annotations of bacteria under study revealed [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] the presence of various genes for iron (Fe) and sulfur (S) metabolism. In addition to this, aromatic compound degradation, stress response and metal resistance genes obtained (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e3.1.4. Genomic Nucleotide Analysis (Gene Ontology) (ANI)\u003c/h2\u003e\u003cp\u003eThe gene ontology and genomic nucleotide analysis (ANI) showed the presence of different features compared with other available strains obtained from NCBI [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGeneral features of A.ferrooxidans NTRS-40 genome used in this study including six strains available on NCBI\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003estrain\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGenome size (bp)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eG\u0026thinsp;+\u0026thinsp;C\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eContigs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCDSs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003erRNA\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003etRNA\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eHit%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA.fxdn NTRS-40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3,257,037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e58.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3,283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA. fxdn ATCC 23270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,982,397\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e58.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3,042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA.frvorns No-37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3,207,552\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3,250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA.fdur ATCC33020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,921,399\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e58.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3,033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA.ferriphilus M20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,667,881\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e58.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2,641\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA. ferrianus MG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e316,586\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e58.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3,083\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA. al DSM 14366\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3,503,318\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e52.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3,596\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAfter the analysis of 16S rRNA gene sequence using EZBiocloud software, different categories of clustered strains of the bacterium has been seen [19. 20]. These were \u003cem\u003eA. ferriphilus M20\u003c/em\u003e, \u003cem\u003eA. ferrivoransNO-37\u003c/em\u003e, \u003cem\u003eA. ferridurans ATCC33020\u003c/em\u003e, \u003cem\u003eA. ferrooxidans ATCC 23270\u003c/em\u003e, \u003cem\u003eA. ferriansus MG and\u003c/em\u003e A. \u003cem\u003ealbertensis DSM 14366\u003c/em\u003e. This result was similar to a study done by [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. ANI analysis showed that there is strong similarity between the strain under study and \u003cem\u003eAcidithiobacillus ferrooxidans\u003c/em\u003e ATCC 23720 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows a heatmap and dendrogram illustrating the genetic clustering of Acidithiobacillus strains, highlighting their similarity levels and diversity, aiding in microbiology and evolutionary biology research.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAverage nucleotide identity Analysis of Acidithiobacillus\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSTRAIN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMG\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDSM 14366\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eM20\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNO-37\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eATCC 23270\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eYNTRS 40\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eATCC 33020\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eA. ferrianus MG\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eA. albertensis dsm 14366\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e97.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eA. ferriphilus m20\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e98.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e97.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eA. ferrivorans no-37\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e98.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e97.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e99.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eA. ferrooxidans atcc 23270\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e97.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e97.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e98.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e97.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eA. ferrooxidans yntrs 40\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e97.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e97.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e98.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e97.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eA. ferridurans atcc 33020\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e98.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e97.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e99.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e98.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e98.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e98.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e3.1.5. Genomic analysis of Heavy metal binding, transport and resistance genes.\u003c/h2\u003e\u003cp\u003eThe genome of \u003cem\u003eAcidithiobacillus ferrooxidans NTRS-40\u003c/em\u003e revealed different genes related to heavy metal binding and responsible for utilization as energy source. Sometimes these genes were lead in the activity of biomining as a result of bioremediation of heavy metals and toxic elements. During the analysis different heavy metal binding genes were identified using RAST software [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Among the genes analysed using the software, some of them are listed (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Up on the analysis 22 genes of heavy metal or element binding genes or proteins were identified as in bacteria under study. Out of these, 5 of them have no specific genes, only binding proteins were identified. They were 3 4Fe-4S ferredoxin, iron-sulfur binding proteins and 2 heavy metal binding proteins. From the identified genes, 3 genes were Molybdenum binding (ModC and 2Mod A), 2 Zinc binding (ZnuA and ZnuC), 7 Iron binding (TonB, 2HesB_2IscA_2SufA), 1 Mercury binding (MerP), and 4 Phosphate binding genes (PstB, PstS, PhnK and PhnL) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eLarge number of genes responsible for resistance to toxic compounds and heavy metals were identified using genome analysis of the bacterium (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). A number of genes important in heavy metal resistance and binding were observed in the membrane transport (ABC transporter system) and periplasmic membrane (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Heavy metal transport system proteins and genes analysed from the bacterium under study was Iron and ferric transport genes and proteins (\u003cem\u003eTonB, FeoB\u003c/em\u003e and \u003cem\u003eTonB\u003c/em\u003e-dependent receptor), magnesium and cobalt transport protein (\u003cem\u003eCorA\u003c/em\u003e), Managanese transport protein (\u003cem\u003eMntH\u003c/em\u003e), Mercuric transport protein (\u003cem\u003eMerC\u003c/em\u003e), Mg(2+)-transport-ATPase-associated protein \u003cem\u003e(MgtC\u003c/em\u003e), molybdenum ABC transporter ATP-binding protein \u003cem\u003e(ModC\u003c/em\u003e), molybdenum ABC transporter, substrate-binding protein (\u003cem\u003eModA\u003c/em\u003e), molybdenum transport system protein (\u003cem\u003eModD\u003c/em\u003e), phosphate ABC transporter, ATP-binding protein (\u003cem\u003ePstB\u003c/em\u003e), phosphate ABC transporter, permease protein (\u003cem\u003ePstA\u003c/em\u003e), phosphate ABC transporter, permease protein \u003cem\u003e(PstC\u003c/em\u003e), phosphate ABC transporter, substrate-binding protein \u003cem\u003e(PstS\u003c/em\u003e), phosphate transport system regulatory protein (\u003cem\u003ePhoU\u003c/em\u003e), phospholipid ABC transporter shuttle protein (\u003cem\u003eMlaC\u003c/em\u003e), potassium-transporting ATPase A chain (EC 3.6.3.12) (TC 3.A.3.7.1), potassium-transporting ATPase B chain (EC 3.6.3.12) (TC 3.A.3.7.1), potassium-transporting ATPase C chain (EC 3.6.3.12) (TC 3.A.3.7.1), sodium-transporting ATPase subunit G, zinc ABC transporter, ATP-binding protein (\u003cem\u003eZnuC\u003c/em\u003e), zinc ABC transporter, permease protein (\u003cem\u003eZnuB\u003c/em\u003e), zinc ABC transporter, substrate-binding protein (\u003cem\u003eZnuA\u003c/em\u003e) and Copper-translocating P-type ATPase EC 3.6.3.4 for transporting lead, cadmium, zinc and mercury [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn addition to heavy metal transport system, there were heavy metal resistance genes and proteins analyzed from genome of the A.ferrooxidans NTRS-40 bacterium like Arsenic resistance protein (\u003cem\u003eArsH\u003c/em\u003e), Cobalt/zinc/cadmium resistance protein (\u003cem\u003eCzcD\u003c/em\u003e), Cobalt-zinc-cadmium resistance protein, Copper resistance protein (\u003cem\u003eCopC\u003c/em\u003e), Copper resistance protein (\u003cem\u003eCopD\u003c/em\u003e) and Mercuric resistance operon regulatory protein (\u003cem\u003eMerR\u003c/em\u003e) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLists of genes and proteins involved in heavy metals and elements binding Analysis of Acidithiobacillus ferrooxidans NTRS-40\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eHeavy metal and element binding genes and proteins\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGene\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eProteins\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eModC\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMolybdenum-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eModA\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMolybdenum ABC, periplasmic molybdenum-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eZnuA\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eZinc ABC, periplasmic-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eZnuC\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eZinc ABC, ATP-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eIscA\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIron binding protein for iron-sulfur cluster assembly\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eTonB\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFerric siderophore, periplasmic binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHesB_IscA_SufA\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eprobable iron binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHesB_IscA_SufA\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eprobable iron binding protein in Nif operon\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMerP\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePeriplasmic mercury(+\u0026thinsp;2) binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePstB\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhosphate-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePstS\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhosphate ABC, periplasmic phosphate-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePhnK, PhnL\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhosphonates-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows different genes and the proteins they produce, which are involved in binding and transporting various essential elements and heavy metals across the cell membrane. These proteins play important roles in cellular processes and help the cell adapt to different environmental conditions. Each gene is associated with a specific protein and its function, such as binding molybdenum, zinc, iron, and mercury, phosphate, and phosphonate compounds for transport or utilization within the cell [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe chromosomal region of the focus gene (top) is compared with similar organisms. The graph is centered on the focus gene, which is red and numbered and denoted 1. Sets of genes with similar sequence are grouped with the same number and color. Genes whose relative position is conserved in at least four other species are functionally coupled and share gray background boxes. As it was shown by Rasta viewer software, focus gene always points to the right (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHeavy metal transporter and binding proteins and their associated gene\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eheavy metal transporter and binding proteins and their associated gene\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGenes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProteins\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eTonB\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFerric siderophore transport system, periplasmic binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFeoB\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFerrous iron transporter\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCorA\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMagnesium and cobalt transport protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMntH\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eManganese transport protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMerC\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMercuric transport protein,\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMgtC\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMg(2+)-transport-ATPase-associated protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eModC\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMolybdenum ABC transporter ATP-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eModA\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMolybdenum ABC transporter, substrate-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eModD\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMolybdenum transport system protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePstB\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhosphate ABC transporter, ATP-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePstA, PstC\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhosphate ABC transporter, permease protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePstS\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhosphate ABC transporter, substrate-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePhoU\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhosphate transport system regulatory protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMlaC\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhospholipid ABC transporter shuttle protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eZnuC\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eZinc ABC transporter, ATP-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eZnuB\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eZinc ABC transporter, permease protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eZnuA\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eZinc ABC transporter, substrate-binding protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNot Identified\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eABC-type Fe3+-siderophore transport system permease component\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNot Identified\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHeavy metal transport/detoxification protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNot Identified\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLead, cadmium, zinc and mercury transporting ATPase (EC 3.6.3.3) (EC 3.6.3.5); Copper-translocating P-type ATPase (EC 3.6.3.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNot Identified\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePotassium-transporting ATPase A chain (EC 3.6.3.12) (TC 3.A.3.7.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNot Identified\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSodium-transporting ATPase subunit G\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e indicates various genes and the proteins they produce, which are involved in transporting essential elements and heavy metals across bacterial membranes which were summarized from RAST viewer [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. These proteins play crucial roles in the uptake, transport, and detoxification of substances like iron, magnesium, cobalt, manganese, mercury, molybdenum, phosphate, phospholipids, and zinc. They also contribute to the adaptation and survival of bacteria in different environments. Each gene is associated with a specific protein and its function, such as transporting specific ions or molecules across the bacterial membrane.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHeavy metal Resistance genes and associated proteins\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHeavy metal Resistance genes and associated proteins\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eGenes\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eassociated proteins\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eArsH\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eArsenic resistance protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCzcD\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCobalt/zinc/cadmium resistance protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCzcD\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCobalt/zinc/cadmium resistance protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCopC\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCopper resistance protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCopD\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCopper resistance protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eMerR\u003c/em\u003e,\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMercuric resistance operon regulatory protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e describes genes and the proteins they produce, which are involved in heavy metal resistance. These proteins play crucial roles in protecting organisms from the toxic effects of these heavy metals, allowing them to survive and adapt in environments with high metal levels. Each gene is associated with a specific protein that helps the organism resist a particular heavy metal, and their functions are essential for the adaptation and survival of the organisms in challenging conditions.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Discussion\u003c/h2\u003e\u003cp\u003eThe \u003cem\u003eA.ferrooxidans NTRS-40\u0026rsquo;s\u003c/em\u003e genome was analysed using different software like EZBiocloud, CLASTAL W, OAT, MEGA 11 and others. The result has confirmed the presence of arrangement of genes and proteins involved in heavy metal resistance. Some of them were metal-binding proteins, metal transporters, metal chelators, metal reductases, and metal-resistant genes. In addition, there were also genes and proteins capable of binding, transporting, reducing and oxidizing for the survival and resistance of the bacteria, which is in the same result with [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFor the average nucleotide identity or ortho OAT ANI analysis and phylogenetic characterization of the Bacterium of the study, the results indicated a relationship with the \u003cem\u003eA.ferrooxidans ATCC 23720.\u003c/em\u003e 16S rRNA gene phylogeny was studied to evaluate the taxonomic position of the bacterium under study within other members, showing a close relationship with \u003cem\u003eA. ferridurans\u003c/em\u003e (98.18%), \u003cem\u003eA. pherriphilus\u003c/em\u003e (98.18%), \u003cem\u003eA. ferrianus\u003c/em\u003e (97.93%), \u003cem\u003eA. ferrivorans\u003c/em\u003e (97.54%) and \u003cem\u003eA. albertensis\u003c/em\u003e (97.73). This phylogenetic tree showed that \u003cem\u003eA.ferrooxidans ATCC 23720\u003c/em\u003e has 100% similarity with bacterium under study. This showed both bacteria were categorized in the same species. But A. albertensis DSM 14366 showed the least similarity with \u003cem\u003eA.ferrooxidans NTRS-40\u003c/em\u003e. But according to [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], bacterial strain \u003cem\u003eA.albertensis DSM 142366\u003c/em\u003e is not outgrouped from the branch.\u003c/p\u003e\u003cp\u003eAccording to the phylogenetic tree, this bacterium was found in outgroup branch of the phylogeny. The bacterium \u003cem\u003eA.ferrooxidans NTRS-40\u003c/em\u003e was branched together with \u003cem\u003eA.ferrooxidans ATCC 23720\u003c/em\u003e with the highest value (100%), indicating it was closely related to the \u003cem\u003eA.ferrooxidans NTRS-40\u003c/em\u003e.They also categorized under the same species when other bacterial groups in this study were in different species.\u003c/p\u003e\u003cp\u003eIn response to heavy metals resistance, the bacterium has developed different genetic mechanisms like heavy metals binding proteins and genes, heavy metals transporting proteins and genes and also heavy metals resistance genes and proteins. This was showed the bacterium can grow and remediate the toxified soils and other environments [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. \u003cem\u003eA.ferridurans ATCC33020\u003c/em\u003e was also reported to have tolerance to heavy metals and capable to remediate the soils as well as environments [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWhen bacterial groups associated with bacteria under study (\u003cem\u003eA.ferrooxidans NTRS-40\u003c/em\u003e) in the phylogenetic tree and Ortho ANI were compared, only A.\u003cem\u003eferroxidans ATCC 23720\u003c/em\u003e strain was related with functional genes during functional gene analysis by RAST software [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. When compared between the two strains with functional gene analysis, \u003cem\u003eA.ferrooxidans NTRS-40\u003c/em\u003e had more functional genes of heavy metal resistance and binding genes. So, from comparative analysis, these bacterial strains (\u003cem\u003eA. ferrooxidans NTRS-40\u003c/em\u003e and \u003cem\u003eA.ferrooxidans ATCC 23720\u003c/em\u003e) are highly involved in biomining and heavy metal binding. This indicated that they play a great role in biomining of heavy metals as heavy metal bioremediation activity. This is supported by [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] the two strains have similar functional genes \u003cem\u003eZunC\u003c/em\u003e and \u003cem\u003ePstB\u003c/em\u003e which involves in binding of Zink and Phosphate compound. In previous study, it was known that the bacterium under study has increased levels of proteins. These proteins were related to LPS synthesis which could be of great importance for heavy metal resistance. Due to this, various microorganism like \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e can accumulate metals on the cell surface through electrostatic interactions with LPS present in its membrane [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e describes different genes and the proteins they produce, which are involved in binding and transporting essential elements and heavy metals across cell membranes, bacterial membranes, and providing resistance to heavy metals. These proteins play vital roles in cellular processes, bacterial adaptation, and protecting organisms from the toxic effects of heavy metals, enabling survival in challenging environments. Each gene is associated with a specific protein and function, such as binding, transporting, or providing resistance to particular ions or molecules, essential for cellular and bacterial survival and adaptation.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eGenomic and functional analysis of \u003cem\u003eA. ferrooxidans ATCC NTRS-40\u003c/em\u003e revealed that they are highly capable of avoiding the toxicity of heavy metals in their surroundings. The majority of the heavy metal-exposed proteins in \u003cem\u003eA. ferrooxidans NTRS-40\u003c/em\u003e are linked to other bacterial strains, especially \u003cem\u003eA. ferrooxidans ATCC 23720\u003c/em\u003e. Given the challenges in doing conventional genetic research on this microbe, bioinformatics analysis of the entire genome of \u003cem\u003eA. ferrooxidans NTRS-40\u003c/em\u003e offers a useful tool for gene identification and functional gene prediction. A comprehensive understanding of this bacterial gene composition, transport systems, heavy metal resistance, heavy metal binding, and metabolic capacity can be obtained by a genome study. These cellular functions underpin the essential traits of \u003cem\u003eA. ferrooxidans\u003c/em\u003e that relate to its application in commercial biomining, such as its capacity to oxidize iron and sulphur, withstand low pH, and survive in settings that contain potentially hazardous organic and inorganic substances. Additionally, they imply that it can move metals from the cell to the surroundings, which would help the bioleaching of copper, zinc, mercury, molybdenum, cobalt, and other heavy metals. Additionally, the research generated a number of predictions that may prove helpful in understanding biomining systems.\u003c/p\u003e\u003cp\u003eFinally, the study reviewed that \u003cem\u003eA.ferrooxidans\u003c/em\u003e ATCC 23720 is the most closely related strain to the bacterium under study, with 100% similarity in average nucleotide identity (ANI). Additionally, further researches will be important to analyze the practical application of these identified functional genes in heavy metal binding, transporting and resisting heavy metals in different areas, such as industries.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no funding support for this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe submitted version of the paper was approved by all authors who contributed equally.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRamos-Z\u0026uacute;\u0026ntilde;iga J, Gallardo Sebasti\u0026aacute;n, Mart\u0026iacute;nez-Bussenius Crist\u0026oacute;bal, Norambuena R, Navarro CA, Paradela A, Jerez CA (2018) Response of the biomining \u003cem\u003eAcidithiobacillus ferrooxidans\u003c/em\u003e to high cadmium concentrations. J Proteom. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jprot.12.013\u003c/span\u003e\u003cspan address=\"10.1016/j.jprot.12.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLuo H, Shen L, Yin H, Li Q, Chen Q, Luo Y, Liao L, Qiu G (2009) and X. Liu. Comparative genomic analysis of \u003cem\u003eAcidithiobacillus ferrooxidans\u003c/em\u003e strains using the \u003cem\u003eA. ferrooxidans\u003c/em\u003e ATCC 23270 whole-genome oligonucleotide microarray School of Minerals Processing and Bioengineering, Central South University, Changsha, Hunan 410083, China\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang X, She S, Dong W, Niu J, Liang YXY, Liu X, Zhang X, Fan F (2016) Huaqun Yin. Comparative genomics unravels metabolic differences at the speciesand/or strain level and extremely acidic environmental adaptation often bacteria belonging to the genus Acidithiobacillus. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.syapm.2016.08.007\u003c/span\u003e\u003cspan address=\"10.1016/j.syapm.2016.08.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTran TTT, Mangenot S, Magdelenat G, Payen E, Rouy Z, Belahbib H, Grail BM, Johnson DB, Bonnefoy V, Talla E (2017) Comparative Genome Analysis Provides Insights into Both the Lifestyle of Acidithiobacillus ferrivorans Strain CF27 and the Chimeric Nature of the Iron-Oxidizing Acidithiobacilli Genomes. Front Microbiol 8:1009. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fmicb.2017.01009\u003c/span\u003e\u003cspan address=\"10.3389/fmicb.2017.01009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnila Fariq JC, Blazier A, Yasmin, Terry J (2019) Gentry \u0026amp; Youjun Deng. Whole genome sequence analysis reveals high genetic variation of newly isolated \u003cem\u003eAcidithiobacillus ferrooxidans\u003c/em\u003e IO. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-019-49213-x\u003c/span\u003e\u003cspan address=\"10.1038/s41598-019-49213-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. -2C\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang Y, Zhang S, Zhao D, Ni Y, Wang W Lei Yan. Complete genome sequence of Acidithiobacillus ferrooxidans YNTRS-40, a strain of the ferrous iron and sulfur-oxidizing acidophile 2019, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.21203/rs.2.17384/v1\u003c/span\u003e\u003cspan address=\"10.21203/rs.2.17384/v1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang X, Liu Z, Wei G, Yang F, Liu X In Silico Genome-Wide Analysis Reveals the Potential Links Between Core Genome of Acidithiobacillus thiooxidans and Its Autotrophic Lifestyle. Front Microbiol 2018 9:1255. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fmicb.2018.01255\u003c/span\u003e\u003cspan address=\"10.3389/fmicb.2018.01255\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKapilesh Jadhav \u0026middot; Bijayendra Kushwaha (2021) \u0026middot; Indrani Jadhav \u0026middot; Prem Shankar \u0026middot; Anjali Geethadevi \u0026middot; Gaurav Kumar \u0026middot;Sonam Mittal \u0026middot; Guru Prasad Sharma \u0026middot; Madhuri Parashar,\u0026middot; Deepak Parashar, Genomic analysis of a novel species \u003cem\u003eHalomonas shambharensis\u003c/em\u003e isolated from hypersaline lake in Northwest India. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11033-020-06131\u003c/span\u003e\u003cspan address=\"10.1007/s11033-020-06131\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJorge Vald\u0026eacute;s I, Pedroso R, Quatrini RJ, Dodson H, Tettelin R, Blake II, Jonathan A, Eisen, David S, Holmes (2008) \u003cem\u003eAcidithiobacillus ferrooxidans metabolism\u003c/em\u003e: from genome sequence to industrial applications. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://creativecommons.org/licenses/by/2.0\u003c/span\u003e\u003cspan address=\"http://creativecommons.org/licenses/by/2.0\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJiri Kucera O, Sedo D, Potesil O, Janiczek Z, Zdrahal M, Mandl (2016) Comparative proteomic analysis of sulfur-oxidizing Acidithiobacillus ferrooxidans CCM 4253 cultures having lost the ability to couple anaerobic elemental sulfur oxidation with ferric iron reduction. Res Microbiol. \u003cdiv class=\"ExternalRefDOI\"\u003ehttp://dx.doi.org/10.1016/\u003c/div\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen J, Liu Y, Diep P, Mahadevan R (2021) Genomic Analysis of a Newly Isolated Acidithiobacillus ferridurans JAGS Strain Reveals Its Adaptation to Acid Mine Drainage. Minerals 11:74. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/min11010074\u003c/span\u003e\u003cspan address=\"10.3390/min11010074\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarold Nu\u0026thinsp;~\u0026thinsp;nez PC, Covarrubias A, Moya-Beltr!an F, Issotta LG, Acu\u0026thinsp;~\u0026thinsp;na DB, Johnson (2016) Raquel Quatrini. Detection, identification and typing of Acidithiobacillus species and strains:a review. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.resmic.2016.05.006\u003c/span\u003e\u003cspan address=\"10.1016/j.resmic.2016.05.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDan Zhao \u0026middot; Jian Yang \u0026middot; Tao Liu \u0026middot; Dong Lu \u0026middot; Shuang Zhang \u0026middot; Lei Yan \u0026middot; Yongqing Ni. Complete Genome Sequence Analysis of \u003cem\u003eAcidithiobacillus ferrivorans\u003c/em\u003e XJFY6S-08 Reveals Environmental Adaptation to Alpine Acid Mine Drainage. (2021) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00284-021-02423-x\u003c/span\u003e\u003cspan address=\"10.1007/s00284-021-02423-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLinda Dekker F, Arsene-Ploetze JM, Santini (2015) Comparative proteomics of Acidithiobacillus ferrooxidans grown in the presence and absence of uranium. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.resmic.2016.01.007\u003c/span\u003e\u003cspan address=\"10.1016/j.resmic.2016.01.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRui Liu L, Ma H, Wang D, Liu X, Lu X, Huang (2023) Shanshan Huang and Xueduan Liu. Comparative genomics reveals intraspecific divergence of \u003cem\u003eAcidithiobacillus ferrooxidans\u003c/em\u003e: insights from evolutionary adaptation. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1099/mgen.0.001038\u003c/span\u003e\u003cspan address=\"10.1099/mgen.0.001038\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang S (2018) \u0026middot; Lei Yan \u0026middot; Weijia Xing \u0026middot; Peng Chen \u0026middot; Yu Zhang \u0026middot; Weidong Wang. \u003cem\u003eAcidithiobacillus ferrooxidans\u003c/em\u003e and its potential application. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00792-018-1024-9\u003c/span\u003e\u003cspan address=\"10.1007/s00792-018-1024-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnjana, Pandey (2011) Anand Srivastava and Ashutosh Pandey. \u003cem\u003eAcidithiobacillus ferrooxidans\u003c/em\u003e: A bioleaching bacteria for better iron (II) oxidation ability. Int J Innovations Biol Chem Sci 1:32\u0026ndash;37\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCarro L, Veyisoglu A, Guven K, Schumann P, Klenk H-P, Sahin N (2022) Genomic Analysis of a Novel Heavy Metal Resistant Isolate from a Black Sea Contaminated Sediment with the Potential to Degrade Alkanes: Plantactinospora alkalitolerans sp. nov. Diversity 14:947. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/d14110947\u003c/span\u003e\u003cspan address=\"10.3390/d14110947\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYue Zhan \u0026middot; Mengran Yang \u0026middot; Shuang Zhang \u0026middot; Dan Zhao \u0026middot; Jiangong Duan \u0026middot; Weidong Wang \u0026middot; Lei Yan. Iron and sulfur oxidation pathways of Acidithiobacillus ferrooxidans. (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11274-019-2632-y\u003c/span\u003e\u003cspan address=\"10.1007/s11274-019-2632-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYoon S, Ha S, Lim J, Kwon S, Chun J (2017) A large-scale evaluation of algorithms to calculate average nucleotide identity. Antonie Van Leeuwenhoek 110(10):1281\u0026ndash;1286. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10482-017-0844-4\u003c/span\u003e\u003cspan address=\"10.1007/s10482-017-0844-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee I, Chalita M, Ha S, Na S, Yoon S, Chun J (2017) ContEst16S: An algorithm that identifies contaminated prokaryotic genomes using 16S RNA gene sequences. Int J Syst Evol MicroBiol 67(6):2053\u0026ndash;2057. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1099/ijsem.0.001872\u003c/span\u003e\u003cspan address=\"10.1099/ijsem.0.001872\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee I, Kim O, Park Y, S., Chun J, OrthoANI (2016) An improved algorithm and software for calculating average nucleotide identity. Int J Syst Evol MicroBiol 66(2):1100\u0026ndash;1103. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1099/ijsem.0.000760\u003c/span\u003e\u003cspan address=\"10.1099/ijsem.0.000760\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOverbeek R (2005) The subsystems approach to genome annotation and its use in the project to annotate 1000 genomes. Nucleic Acids Res 33(17):5691\u0026ndash;5702. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/nar/gki866\u003c/span\u003e\u003cspan address=\"10.1093/nar/gki866\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRapid annotation using subsystem technology (RAST) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://rast.nmpdr.org/rast.cgi\u003c/span\u003e\u003cspan address=\"https://rast.nmpdr.org/rast.cgi\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNational Center for Biotechnology Information (NCBI) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"No Funding","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"A.ferrooxidans, biomining, heavy metal, binding, genes","lastPublishedDoi":"10.21203/rs.3.rs-7982109/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7982109/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe majority of microorganisms cannot endure extreme conditions, including heavy metals, high salinity, acidity, alkalinity, and various stress factors. However, only a few can endure extreme environments, with the genus \u003cem\u003eAcidithiobacillus\u003c/em\u003e being widely recognized. Studies have been conducted to demonstrate how proteomic alterations occur in reaction to heavy metals like copper, zinc, nickel, cadmium, potassium, iron, molybdenum, and arsenic. Entire genome sequencing of various \u003cem\u003eAcidithiobacillus\u003c/em\u003e species has revealed new understandings of their roles. Four distinct functional gene categories were thoroughly examined for their capacity to bind heavy metals in the context of biomining applications. The complete genome sequence acquired was annotated and examined with Ezbiocloud software. Subsequently, utilizing the 16S rRNA gene sequence of the \u003cem\u003eA. ferrooxidans YNTRS-40\u003c/em\u003e strain, the sequence's purity was evaluated through cont16s rRNA provided by EZbiocloud. Based on the phylogeny derived, two extremes were noted: one being the nearest strain, \u003cem\u003eA. ferrooxidans ATCC 23720\u003c/em\u003e, and the other being the outgroup, \u003cem\u003eA. albertensis DSM 14366.\u003c/em\u003e Twenty-two distinct heavy metal binding genes were examined using RAST annotation software. The genes included were \u003cem\u003eMod, ZnuA, ZnuC, MerP, SufA, PstB, PstS, PhnK, PhnL, FeoB, MntH, MerC, MgtC\u003c/em\u003e, and \u003cem\u003ePhoU\u003c/em\u003e. The analyzed bacteria with these genes were recognized as having the potential for application in heavy metal bioremediation.\u003c/p\u003e","manuscriptTitle":"Comparative genome and protein analysis for Acidithiobacillus ferrooxidans strains in terms of heavy metal binding as an application for biomining","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-30 07:25:23","doi":"10.21203/rs.3.rs-7982109/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"958d43d7-eea6-4960-ac64-772786b878f2","owner":[],"postedDate":"October 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57111387,"name":"Biotechnology and Bioengineering"}],"tags":[],"updatedAt":"2025-10-30T07:25:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-30 07:25:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7982109","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7982109","identity":"rs-7982109","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}