Since the industrial revolution, new ecological niches have emerged following the release of toxic industrial wastes, which often consist of a mixture of heavy metals, organic compounds, and hydrocarbons, into the environment. Environmental pollution is a significant problem, affecting many environments in a negative and almost irreversible way (Filali et al. 2000). In particular, heavy metal contamination of surface waters directly impacts both the environment and public health (Chihomvu et al. 2015). Environmental bacteria that are resistant to heavy metals, as well as multiple antibiotics, are of great concern in many areas of the world.
Bacteria-heavy metal interactions have been studied in many and extreme environments. Some metals are essential cofactors of specific proteins; others cause oxidative stress because of their redox potential. Heavy metals are naturally occurring, but with excessive anthropogenic activities, they are shown in large quantities, then become toxic at high concentration. Soil, water, and air are the major environmental compartments, which are affected by heavy metals pollution leading to many adverse impacts (Tchounwou et al. 2012).
In this study, we focused on copper, silver, and mercury. These heavy metals are more and more used in many applications and are also found in different areas worldwide (Kerfoot et al. 2002; 2004).
Copper is an essential element that is toxic at high concentrations (Chihomvu et al. 2015). High cytoplasmic copper concentrations can lead to dysfunctional proteins (Kershaw et al. 2005), or damage lipids, DNA, and other molecules (Harrison et al. 2000). Microorganisms have developed several copper resistance mechanisms to survive in contaminated environments.
Silver is used as an antimicrobial agent in various medical products, such as catheters, and for burns wound treatments (Silver and Phung 1996; Klasen 2000; Jung et al. 2008). Bacteria can develop resistance to silver via efflux mechanisms encoded by the
The mercury ion has been known to be effective against a broad range of microorganisms. It has no beneficial functions in living organisms, and this toxic compound can accumulate in the food chain (Jan et al. 2009). The mercury resistance system is encoded by the
Furthermore, many reports suggested that heavy metal contamination could directly or indirectly impact the maintenance and proliferation of antibiotic resistance (Summers 2002). Several studies reported the co-occurrence of heavy metal and antibiotic resistance. It has been proven that heavy metals in environmental reservoirs, water, wastewater, and soil, may contribute to the selection of antibiotic-resistant strains through co-resistance and cross-resistance mechanisms (Nguyen et al. 2019). It is important to underline that co-resistance occurs when genes coding for the resistance phenotypes are present on the same mobile genetic elements (i.e., plasmids, transposons, and integrons) (Mandal et al. 2016). Mercury, copper, and silver resistance genes are located on mobile genetic elements, e.g., on class II transposons with various antibiotic resistance genes. For instance,
In this report, we were interested in studying the contamination of ten sites in Tunisia by silver, copper, and mercury and detecting a cross-resistance between them and antibiotics in water environmental isolates. It was done to understand better whether heavy metal contamination could contribute to the proliferation and the spread of antibiotic resistance.
Sampling sites characteristics, locations, and their corresponding geographic coordinates.
Sites/numeration | Geographic coordinates | Location | Characteristics |
---|---|---|---|
Menzel Jemil, Bizerte: Site I | 37°14′19″N, | Industrial area | Waste and contamination from the textile industry and wiring throwing inside the Bizerte lagoon |
Menzel Bourguiba, Bizerte: Site II | 37°09′N, 9°47′E | Unit manufacturing printed circuits. In the Iron factory | Contamination by HM from the iron factory in the Bizerte lagoon. Urban and agricultural pollution |
Tinjah wedi, Bizerte: Site III | 37°10′N, 9°45′E | Near the lagoon of Bizerte | Agricultural pollution and compost contamination. |
Beja: Site IV | 36°43′30″N, | Southwest of the city of Tunis Near the CWTP* | Urban and industrial area, the most known are wastewater and yeast factory |
Essijoumi Lagoon: Site V | 36°45′52″N, | Contribution in the Gulf of Tunis | Lagoon receiving contamination from wastewater contamination and wastes from the capital Tunis. |
Rades Milian River: Site VI | 36°46′N, | Industrial zone of Rades | High load alluvial estimated at 25 grams per liter. Receiving wastewater from two towns Rades and Ezzahra. |
Majerda River: Site VII | 37°7′0″N, | A peninsula in far north-eastern Tunisia | Used for irrigation of the region’s agriculture |
Lebna River: Site VIII | 36°45′N, | Inlet manifold sewage treatment plant | Agricultural coastal Plans can be found in the area of Cap Bon |
Om Larayes, Gafsa: Site IX | 34°28′59″N, | The industrial platforms of phosphgyps activity | One of the known mining towns in Gafsa |
Gulf of Gabes: Site X | 34°05′37″N, | The junction between the Eastern and Central Basin | Known by industry for the transformation of merchantable phosphate into Phosphoric Acid (H3PO4) and Chemical Fertilizers |
– CWTP: Collector between wastewater treatment plant.
Primers, expected fragment size and conditions of PCR experiments used for β-lactams resistance encoding genes.
Multiplex | Target | Primers sequences (5′–3′) | Size (pb) | Concentration (pmol/µl) | Volume (µl) | Amplification conditions |
---|---|---|---|---|---|---|
1 | TEM | MultiTSO-T_F CATTTCCGTGTCGCCCTTATTC | 800 | 0.4 | 0.4 | 94°C 10 min 94°C 40 sec 60°C 40 sec 30 cycles 72°C 1 min 72°C 7 min |
MultiTSO-T_R CGTTCATCCATAGTTGCCTGAC | 0.4 | 0.4 | ||||
SHV | MultiTSO-S_F AGCCGCTTGAGCAAATTAAAC | 713 | 0.4 | 0.4 | ||
MultiTSO-S_R ATCCCGCAGATAAATCACCAC | 0.4 | 0.4 | ||||
OXA-1-like | MultiTSO-O_F GGCACCAGATTCAACTTTCAAG | 564 | 0.4 | 0.4 | ||
MultiTSO-O_R GACCCCAAGTTTCCTGTAAGTG | 0.4 | 0.4 | ||||
2 | CTX-M group 1 | MultiCTXMGp1_F TTAGGAARTGTGCCGCTGTA | 688 | 0.4 | 0.4 | |
MultiCTXMGp1_R CGATATCGTTGGTGGTCCCAT | 0.2 | 0.2 | ||||
CTX-M group 2 | MultiCTXMGp2_F CGTTAACGGCACGATGAC | 404 | 0.2 | 0.2 | ||
MultiCTXMGp1_R CGATATCGTTGGTGGTTCCAT | 0.2 | 0.2 | ||||
CTX-M group 9 | MultiCTXMGp9_F TCAAGCCTGCCGATCTGGT | 561 | 0.4 | 0.4 | ||
MultiCTXMGp9_R TGATTCTCGCCGCTGAAG | 0.4 | 0.4 | ||||
CTX-M group 8 | CTX-Mg8/25_F AACTCCCAGACGCTCTAC | 326 | 0.4 | 0.4 | ||
CTX-Mg8/25_R TCGAGCCGGAASGTGTAAT | 0.4 | 0.4 |
Simplex | Target | Primers sequences (5′– 3′) | Size (pb) | Concentration (pmol/µl) | Volume (µl) | Amplification conditions |
---|---|---|---|---|---|---|
1 | OXA-48 | MultiOXA-48_F GCTTGATCGCCCTCGATT | 281 | 0.4 | 0.4 | 94°C 10 min 94°C 40 sec 57°C 40 sec 30 cycles 72°C 1 min 72°C 7 min |
MultiOXA-48_R GATTTGCTCCGTGGCCGAAA | 0.4 | 0.4 |
Primers, expected fragment size, and conditions of PCR experiments used for quinolones resistance encoding genes.
Multiplex | Target | Sequence of primer (5′–3′) | Size (bp) | Amplification conditions |
---|---|---|---|---|
3 | qnrA_FCAGCAAGAGGATTTCTCACG | 630 | 95°C 15 min 94°C 30 sec 63°C 40 sec 30 cycles 72°C 90 sec 72°C 10 min | |
qnrA_RAATCCGGCAGCACTATTACTC | ||||
qnrB_FGGCTGTCAGTTCTATGATCG | 488 | |||
qnrB_RGAGCAACGATGCCTGGTAG | ||||
qnrC_FGCAGAATTCAGGGGTGTGAT | 118 | |||
qnrC_RAACTGCTCCAAAAGCTGCTC | ||||
qnrD_FCGAGATCAATTTACGGGGAATA | 581 | |||
qnrD_RAACAAGCTGAAGCGCCTG | ||||
qnrS_FGCAAGTTCATTGAACAGGGT | 428 | |||
qnrS_RTCTAAACCGTCGAGTTCGGCG |
Phylogenetic tree based on the partial 16S rRNA gene sequences of the 39 isolates. Ten colors used to distinguish ten different sampling sites classified from north to south of Tunisia: Dark blue: Menzel Jemil; Orange: Iron factory; Red: Tinjahwedi Bizerte; Cyan: Collector between wastewater treatment plant (CWTP) of Beja; Green: Marsh Sejoumi; Yellow: Milian Rades Wedi; Light purple: Majerda River; Pink: Lebnawedi Cap Bon; Dark purple: Om Larayes Gafsa; Grey: Golf of Gabes.
The growth of strains was inhibited at the copper concentrations starting from 3 to 6 mM. Copper resistance in relation with sites was as follows: 100% of sensible isolates were detected in Majerda River showing MIC values from 0.75 to 1.5 mM; < 80% of sensible isolates were detected in Gafsa (about four from a total of five isolates), which demonstrated the lowest MIC values from 0.625 to 1.5 mM; < 50% of sensible isolates were detected in Essijoumi Lagoon with MIC values similar to that of the isolates from Gafsa; < 25% of isolates were detected in each site with MIC values ranged from 0.625 to 1.5 mM. As a result, 75% of isolates resistant to copper were detected in the following Sites: I, II, III, IV, VI, IX, and X followed by 50% of the resistant isolates detected in Site V, and 20% of the isolates were detected in Gafsa (Site VIII). However, none of the isolates resistant to copper were detected in Majerda River (Site VII). Resistant and sensible isolates were detected with different percentages from one site to another as follows: 100% of isolates were detected in Lebna wedi Cab Bon with a low MIC: equal to 0.005 mM; < 75% of isolates detected in Gulf of Gabes were sensible to mercury with the MIC values ranged from 0.0025 to 0.008 mM; < 50% of sensible isolates were isolates from Bizerte (Site I, II, and III) with the MIC values ranged from 0.0025 to 0.005 mM; < 40% of isolates were sensible to mercury with the MIC values equal to 0.005 mM belonged to Site VIII; <33% sensible isolates collected from Collector between wastewater treatment plant (CWTP) of Beja, Melian Rades Wedi, and Majerda River. All isolates collected from Essoujimi River were resistant to mercury with the MIC values equal to 0.08 mM.
A high percentage of resistance to silver was shown for 92.30% of the total isolates. Furthermore, 22 isolates (56.41%) showed high resistance to copper, and about half of the isolates (51.28%) showed high resistance to mercury.
Detection by PCR of heavy metal resistance genes.
a – Amplicon of
b – Amplicon of
c – Amplicon of
M – Size Marker 1 kb Plus.
Phenotypic and molecular characteristics of antibiotic and heavy metal resistant isolates collected from polluted water in Tunisia.
Strains | Sites | MICs of HM (µg/ml) Ag2+ Cu2+ Hg2+ | HM resistance genes | AB resistance profile | AB resistance genes |
---|---|---|---|---|---|
MJ. Bizerte | 0.064 (R) 0.625(S) 0.08 (R) | AMP, ATM, FOS | |||
MJ. Bizerte | 0.064 (R) 3 (R) 0.005 (S) | AMP, CAZ | |||
MJ. Bizerte | 0.064 (R) 6 (R) 0.0025 (S) | AMP, TIC, PIP, CXM, CFM, CAZ, ATM, GMN, NET, TOB, CTX | |||
MJ. Bizerte | 0.064 (R) 3(R) 0.08 (R) | AMP, ATM, FOS, CIP, LEV | |||
IF of Bizerte MB | 0.032 (R) 3(R) 0.08 (R) | AMP, ATM, FOS | |||
IF of Bizerte MB | 0.064 (R) 6(R) 0.005 (S) | AMP, CAZ, SXT, CHL | |||
IF of Bizerte MB | 0.064 (R) 3(R) 0.08 (R) | AMP, TIC, FOX, FEP, ETP, AMC, CAZ, IMP, SXT, CTX, FOS, CLS, NOR, CIP, GMN, AKN, NET, TOB, NFE, MNO, TET | |||
IF of Bizerte MB | 0.064 (R) 1.5 (S) 0.005 (S) | AMP, TIC, TCC, PIP, FEP, CAZ, ATM, FOS | |||
IF of Bizerte MB | 0.064 (R) 3 (R) 0.005 (S) | AMP, CAZ | |||
Tinjah wedi, Bizerte | 0.064 (R) 1.5 (S) 0.08 (R) | AMP, ATM, FOS | |||
Tinjah wedi, Bizerte | 0.032 (R) 3 (R) 0.005 (S) | AMP, TCC, FOS | |||
Tinjah wedi, Bizerte | 0.064 (R) 3 (R) 0.005 (S) | AMP, CAZ, CHL | |||
Tinjah wedi, Bizerte | 0.032 (R) 3 (R) 0.04 (R) | AMP, TIC, AMC, NAL, NOR, CHL, TGC, MNO, TET | |||
CWTP of Beja | 0.064 (R) 3 (R) 0.005 (S) | AMP, TIC, ATM, FOS, IMP, MEM, | |||
CWTP of Beja | 0.064 (R) 1.5 (S) 0.08 (R) | AMP, TIC, TCC | |||
CWTP of Beja | 0.008 (S) 3 (R) 0.04 (R) | AMP, TIC, TCC, PIP, FEP, CAZ, ATM, FOS | |||
Marsh Sejoumi | 0.032 (R) 1.5 (S) 0.08 (R) | AMP, TIC | |||
Marsh Sejoumi | 0.008 (S) 0.625 (S) 0.08 (R) | AMP, CAZ | |||
Marsh Sejoumi | 0.0064(R) 3 (R) 0.08 (R) | AMP, TIC, PIP, TCC, FOS | |||
Marsh Sejoumi | 0.064 (R) 6 (R) 0.08 (R) | AMP, TIC, FOX, AMC, CTX | |||
Milian Rades Wedi | 0.064 (R) 3 (R) 0.02 (R) | AMP, TIC, TCC, PIP, FEP, CAZ, ATM, FOS | |||
Milian Rades Wedi | 0.064 (R) 0.625 (S) 0.08 (R) | AMP, CAZ, SXT, CHL | |||
Milian Rades Wedi | 0.004 (S) 0.625 (S) 0.005 (S) | AMP, ATM, FOS | |||
Majerda River | 0.064 (R) 1.5 (S) 0.005 (S) | AMP, CAZ | |||
Majerda River | 0.064 (R) 1.5 (S) 0.02 (R) | AMP, TIC, FOX, AMC | |||
Majerda River | 0.032 (R) 0.75 (S) 0.02 (R) | AMP, FOS, ATM, LEV | |||
Lebna wedi C.B | 0.064 (R) 3 (R) 0.005 (S) | AMP, TIC, FOX, AMC, TGC, MNO, TET | |||
Lebna wedi C.B | 0.064 (R) 1.5 (S) 0.005 (S) | AMP, TIC, AMC, CTX, CLS | |||
Lebna wedi C.B | 0.032 (R) 3 (R) 0.005 (S) | AMP, CAZ | |||
Lebna wedi C.B | 0.064 (R) 6 (R) 0.005 (S) | AMP, TIC, AMC | |||
Om Larayes, Gafsa | 0.064 (R) 3 (R) 0.08 (R) | AMP, TIC, TCC, PIP, FEP, ATM, IMP, MEM, FOS | |||
Om Larayes, Gafsa | 0.064 (R) 0.625(S) 0.005 (S) | AMP | |||
Om Larayes, Gafsa | 0.064 (R) 1.5 (S) 0.08 (R) | AMP, TIC, FEP, CAZ, ATM | |||
Om Larayes, Gafsa | 0.032 (R) 1.5 (S) 0.08 (R) | AMP, TIC, TCC, PIP, TZP, CAZ, ATM | |||
Om Larayes, Gafsa | 0.0064 (R) 0.75 (S) 0.005 (S) | AMP, TIC, TCC, ATM, MEM | |||
Gulf of Gabes | 0.064 (R) 3 (R) 0.008 (S) | AMP, TIC, TCC, PIP, TZP, ATM, MEM | |||
Gulf of Gabes | 0.064 (R) 1.5 (S) 0.005 (S) | AMP, FOX, AMC, TGC, MNO, TET | |||
Gulf of Gabes | 0.0064 (R) 6 (R) 0.08 (R) | AMP, TIC, TCC, PIP, TZP, FEP, CAZ, ATM, MEM, LEV, FOS | |||
Gulf of Gabes | 0.032 (R) 3 (R) 0.0025 (S) | AMP, TIC, TCC, PIP, CFN, CXM, CFM, CAZ, FEP, ATM, GMN, NET, TOB |
AKN – Amikacin; AMC – Amoxicillin-Clavulanic acid; ATM – Aztreonam; CAZ – Ceftazidim; CFM – Cefixim; CFN – Cefalexin; CHL – Chlorampenicol; CIP – Ciprofloxacin; CLS – Colistin; CTX – Cefotaxim; CXM – Cefuroxim; ETP – Ertapenem; FEP – Cefepim; FOS – Fosfomicin; FOX – Cefoxitin; GMN – Gentamicin; IMP – Imipenem; LEV – Levofloxacin; MEP – Meropenem; MNO – Minocyclin; NAL – Nalidixic acid; NET – Netilmecin; NMN – Neomycin; PIP – Piperacillin; SXT – Trimethoprim-Sulfamethoxazole; TCC – Ticarcillin-Clavulanic acid; TET – Tetracycline; TGC – Tigecyclin; TIC – Ticarcillin; TOB – Tobramycin; TZP – Piperacillin-Tazobactam;
The mercuric reductase gene
Sequence alignment of the partial SilE protein from 39 isolates with SilE from pMG101 (SilE AAD11743). Letters shows res idues different from the consensus. Conserved histidine and methionine residues are marked above with either a circle or a square, respectively.
The complete sequence of CusA efflux pump of the
A similar partial CusA sequences from
Similar partial CusA sequence was showed for
Sequence alignment of the partial Cation efflux system protein CusA from 10 isolates with
Five hundred sixty-one amino acids compose the complete sequence of the mercuric reductase MerA protein of
Sequence alignment of the partial mercuric reductase protein MerA from 8 isolates with
Same different residues like in
In order to investigate the spread and emergence of environmental bacteria resistant to heavy metals in contaminated waters, we studied the heavy metal-resistant phenotype and selected marker genes for resistance to silver, mercury, and copper. In addition, we scored antibiotic resistance to evaluate the impact of heavy metal contamination as a selective agent in the spreading of antibiotic resistance. The heavy metals in the collected contaminated waters from ten sites over Tunisia mainly originated from anthropogenic activities. Sites I, II, and III, located near and surround the Lagoon of Bizerte, were subjected to urban and agricultural pollutions. As described by (Dellali et al. 2001), agricultural origin wastes reach the lagoon due to leaching of inland cultivated and devoted to cereal activities (Banni et al. 2009). With the thirteen isolates collected from Sites I, II, and III, the highest resistance was recorded for silver; 100% of isolates showed the high MIC values for Ag+ ranging from 0.032 to 0.064 mM, and harbored the
On the other hand, we found the
Data recorded in Essijoumi Lagoon showed that 50% of isolates collected in this site harbored the
No data in the literature evokes the contamination of this site by mercury. Nevertheless, 100% of isolates in this site harbored the
Site VI and VII are located on the west coast of Tunis’s gulf and exposed to heavy metals, mainly transported to the marine environment (Ben Amor et al. 2019). The geoaccumulation index value for copper (10 ppm) recorded by (Ben Amor et al. 2019) has indicated that all samples were uncontaminated. Those results explained in the present work, the lowest proportion (20%) of isolates that harbored the
Trace heavy metal, like mercury, is among the most severe pollutants in nature due to its toxicity. Luckily, it was reported by (Ennouri et al. 2008) at a very low concentration (0.33 ppm) in the Lebna River (Site VIII). Regarding Hg, the concentrations are relatively low. It may be why isolates did not develop any resistance, especially that we did not detect the
The leading cause of contamination of waters in Gabes (Site X) is the acidic industrial effluent that originated from the phosphate treatment factory. Effluents contain phosphogypsum particles and cause ecological risk to marine organisms and human health (Naifar et al. 2018). 75% of isolates from Gabes harbored the cusA gene with the MIC value for copper of 3 mM. When we compare our results with (Naifar et al. 2018) results, we could say that the copper concentration of 0.5 ppm is lower than Tunisian standards (1.5 ppm). It can stimulate the resistance against copper with high MICs. The co-stimulation may explain those results by other heavy metals present with high concentrations, i.e., iron (16 ppm) and Zn (18 ppm). Both values exceeded the Tunisian standards (1 ppm) and (10 ppm), respectively.
The present study provided new information about silver contamination, notably the highest resistance in the ten sites was recorded to silver. The
(Long et al. 2010) suggest a crystal structure of the CusA efflux pump methionine mediated CuI but also AgI heavy metal transport. The
The heavy metal binding-sites are formed by three methionines (M573, M623, and M672) and found above this horizontal helix (Long et al. 2010). The partial sequence aligned with consensus started from AA149 to AA280 with conserved M230 and M271. The latter is one of the four channel pairs, which includes the four methionine pairs (M410 and M501, M403 and M486, M391 and M1009, and M271 and M755) as well as the heavy metal binding-sites formed by the three methionines, facilitating heavy metal transport. The mutations that affected the other residues, which did not touch the heavy metal binding-sites or the channel, conserved their functionality in absorbing AgI and CuI ions.
The mercury reductase MerA is known as an enzyme, reducing the ionic mercury Hg (II) to elemental mercury. In bacteria, the mercury resistance is specified by operon (
The MerA amino acid sequences’ multiple alignments in the present study revealed a minor difference in sequence patterns between our MerA protein isolates and the consensus (Fig. 5). Thus, the partial MerA sequence did not contain both motifs. Despite the few mutations, mercuric reductase from our resistant isolates retained the ability to reduce mercury. We suppose that FAD/NADP and mercury binding sites were well conserved in our eight resistant isolates. Among 51.2% of mercury-resistant isolates, which detected the
The overuse of antibiotics in clinics and hospitals raises the emergence of resistant bacteria. Environmental bacteria, especially, showed resistance to antibiotics, which were detected in different environmental compartments such as soils, surface water, sediments ground water, and waste-water (Kümmerer 2004).
In the present study, the environmental strains isolated from the ten sites showed high resistance to a large number of antibiotics, and some were even ESBLs and MBLs-producers, which is a global health concern. This ubiquitous detection of antibiotic resistance and resistant genes in isolates indicates the emergence of antibiotic-resistant strains in the golf of Tunis and Gulf of Gabes, which threatens the health of animals and people throughout Tunisia.
Substantial reports suggest that heavy metal contamination represents an indirect selection agent that contributes to the maintenance and spread of antibiotic resistance factors (Baker-Austin et al. 2006). The
It is the first work describing contaminations by copper, silver, and mercury in ten sites in Tunisia. Such data were almost absent in the literature. Moreover, a high degree of heavy metal and antibiotic resistance were found in our isolates. They develop some new mechanisms to eliminate or reduce heavy metals or antibiotics’ impact.
The resistant environmental bacteria in Tunisia are more prevalent than we expected for both antibiotic and heavy metal resistance. The cross-resistance between them made the bacteria better fitted to the environment. It also enhances the danger and the risk of public health. Even though the detailed mechanisms of cross-resistance are unclear, it will be recommended to study the impact of heavy metals on antibiotic resistance in environmental microorganisms. With the extent of pollution, it is valid to study the co-existence of antibiotics and heavy metal resistance and their particular influence on bacteria.