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. 2023 Nov 16;18(11):e0294565. doi: 10.1371/journal.pone.0294565

Study of heavy metal resistance genes in Escherichia coli isolates from a marine ecosystem with a history of environmental pollution (arsenic, cadmium, copper, and mercury)

Ashley S Tseng 1, Marilyn C Roberts 2, Scott J Weissman 3, Peter M Rabinowitz 1,2,4,*
Editor: Ayman Elbehiry5
PMCID: PMC10653420  PMID: 37972039

Abstract

We analyzed whole genome sequences of 308 Escherichia coli isolates from a marine ecosystem to determine the prevalence and relationships of heavy metal resistance genes (HMRGs) and antibiotic resistance genes (ARGs), as well as the presence of plasmid sequences. We screened all genomes for presence of 18 functional HMRGs conferring resistance to arsenic, cadmium, copper, or cadmium/mercury. In subset analyses, we examined geographic variations of HMRG carriage patterns in 224 isolates from water sources, and sought genetic linkages between HMRGs and ARGs in 25 genomes of isolates resistant to antibiotics. We found high carriage rates of HMRGs in all genomes, with 100% carrying at least one copy of 11 out of 18 HMRGs. A total of 173 (56%) of the isolates carried both HMRGs and plasmid sequences. In the 25 genomes of antibiotic-resistant isolates, 80% (n = 20) carried HMRGs, ARGs, and plasmid sequences, while 40% (n = 10) had linked HMRGs and ARGs on their assembled genomes. We found no evidence of geographic variation in HMRG frequency, nor any association between locational proximity to Superfund sites and co-carriage of HMRGs and ARGs. Our study findings indicate that HMRGs are common among E. coli in marine ecosystems, suggesting widespread heavy metal presence in water sources of a region with history of environmental pollution. Further research is needed to determine the role HMRGs play in driving antimicrobial resistance in human pathogens through genetic linkage and the value their detection in environmental bacterial genomes may offer as an indicator of environmental heavy metal pollution.

Introduction

While there has been increasing scientific recognition of the global health threat posed by bacteria resistant to antibiotics, there has been less attention to the fact that many bacteria also carry genes conferring resistance to heavy metal toxicity, and that these heavy metal resistance genes (HMRGs) may interact with genes conferring resistance to antibiotics. Evidence to support this comes from studies showing increased antimicrobial resistance in bacteria from environments contaminated with heavy metals, and a direct relationship between the carriage of HMRGs and the carriage of antibiotic resistance genes (ARGs) [1]. While the spread of ARGs among and between humans and animals is under intense study, less is known about the movement and sources of HMRGs in bacterial environmental reservoirs.

Although many heavy metals are found naturally in the environment, they can also be present at high concentrations as a result of human activities [2, 3]. Exposure to heavy metals at toxic levels can have detrimental effects on the health of humans and animals [2]. Commonly occurring toxic heavy metals relevant to public health include arsenic, cadmium, copper, lead, and mercury [4, 5]. Certain heavy metals, including copper, arsenic, mercury, and lead, have been used in the past as antimicrobial agents to treat and prevent bacterial infections, and some are still being used in agricultural settings today [6, 7]. Bacteria can acquire resistance to heavy metals as an evolutionary adaptation, which in turn may increase resistance to antibiotics [8]. There is a concern that antimicrobial resistance (AMR) may emerge in environments contaminated with heavy metals. There also may be a direct relationship between the carriage of HMRGs and the carriage of ARGs in common bacteria such as Escherichia coli. Consequently, efforts to address AMR may need to consider the role of heavy metals—in addition to the role of plasmids—in the movement of resistance genes through populations and ecosystems.

E. coli is a large and diverse species group of gram-negative bacteria which are found in the intestinal microbiome of humans and animals, as well as in the environment and as contamination in food products [9]. While most strains of E. coli are not harmful to humans, some E. coli strains are opportunistic pathogens which can cause diarrhea, urinary tract infections, respiratory illness and pneumonia, or other illnesses in humans and animals [9]. Because of its widespread nature in the gut of mammals, reptiles, wild avian species, in the environment, and in food, E. coli encounters diverse exposures and adapts to selective pressures [10].

Antibiotic resistance in E. coli is an increasing concern among public health practitioners due to its ability to accumulate genes conferring resistance to many clinically-relevant antimicrobial agents [11]. Studies have shown that there is often linkage between the carriage of ARGs and HMRGs on the same mobile elements [12–15]. A prior exploratory study characterized antibiotic resistance in E. coli samples from water and animal sources in the Salish Sea ecosystem, some of which were sampled from Superfund sites in the region [16]; however, heavy metal resistance was not previously characterized in these samples.

We analyzed a set of E. coli genomes of environmental and animal isolates sampled from a marine ecosystem with a history of environmental pollution in order to 1) characterize the presence of HMRGs, 2) determine if the carriage of HMRGs was associated with geographic location of the isolate, and 3) determine in a subset of isolates that were resistant to antibiotics if the carriage of HMRGs was associated with the carriage of ARGs.

Materials and methods

Data source

This study utilized whole genome sequencing (WGS) data from E. coli collected and isolated in a prior study of E. coli antibiotic resistance in the Salish Sea ecosystem of the Pacific Northwest region in the US [16]. The Salish Sea ecosystem, located between British Columbia in Canada and Washington (WA) in the US, contains a number of Superfund sites designated by the US Environmental Protection Agency as polluted by hazardous waste, including heavy metals [17]. The prior study found varying levels of antibiotic resistance in 308 E. coli isolates from water and animal sources in the Salish Sea ecosystem [16]. A subset of isolates, 25 (8%) were phenotypically resistant to antibiotics and carried known antibiotic resistance genes [16].

E. coli collection and isolation

The details of sampling have been previously described [16]. In brief, fecal samples from harbor seals (Phoca vitulina), harbor porpoises (Phocoena phocoena), river otters (Lontra canadensis), and English sole (Parophrys vetulus), and water samples from the Salish Sea watershed (fresh water from streams near marine beaches and marine water from four quadrants of the Salish Sea and locations near beaches) were collected during 2018–19 [16]. E. coli were isolated from these samples (N = 308) and tested for phenotypic and genotypic antibiotic susceptibility. A total of 224 of the E. coli isolates were from water samples and 84 isolates were obtained from samples of marine mammals. Fecal swabs were collected postmortem from harbor seals and harbor porpoises between Fall 2018 and Fall 2019. Detailed methods and isolates were described previously [18]. All but one live harbor seal fecal samples were collected by the WA Department of Fish and Wildlife staff from marina docks at various locations throughout the Puget Sound, where harbor seals defecate along the coast at haulout sites. The river otter fecal samples were collected from six of their latrine sites along the Duwamish River, Washington (May–September 2018) [16].

All the isolates sampled from the marine water, marine fish, and live seals were analyzed using broth dilution antibiotic susceptibility testing with the SensititreTM Nephelometer (Thermo Fisher Scientific, Waltham, MA, USA) using the manufacturer’s instructions at the WA State Department of Health’s laboratory. The panels were read using the approved Sensititre SWIN software and were also inspected visually by technicians for microbial growth. The minimum inhibitory concentration for each antibiotic in mg/mL was determined using the Clinical and Laboratory Standards Institute interpretive criteria [19]. This allowed each isolate’s susceptibility pattern (susceptible, intermediate resistant, or resistant) to be assigned to the following antibiotics: amikacin, aztreonam, cefepime, cefotaxime, ceftazidime, ciprofloxacin, doripenem, doxycycline, ertapenem, gentamicin, imipenem, levofloxacin, meropenem, minocycline, piperacillin/tazobactam, ticarcillin/clavulanic acid, tigecycline, tobramycin, and trimethoprim/sulfamethoxazole. E. coli from dead seals and porpoises were tested using the bioMérieux VIETK instrument (Durham, North Carolina, US). The E. coli isolated from river otters, fresh water, marine water by beaches, and a rescued seal pup were tested using a standard disk diffusion assay according to the Clinical and Laboratory Standards Institute [19]. Standard E. coli negative and positive controls were included in each assay.

All 308 isolates were forwarded by the WA State Department of Health’s Antimicrobial Resistance Laboratory to the GenomeTrakr program of the Food and Drug Administration for WGS performed using Illumina (Illumina, San Diego, California, US). The sequence data were deposited with links to BioProject accession number PRJNA283914 in the US National Institutes of Health National Center for Biotechnology Information (NCBI) BioProject database (https://www.ncbi.nlm.nih.gov/bioproject/). The NCBI Sequence Read Archive (https://www.ncbi.nlm.nih.gov/sra/) IDs for the 308 included isolates were: SRR11116088, SRR10947731, SRR10451710, SRR11116091, SRR10451712, SRR10451715, SRR10451717, SRR11251337, SRR10451719, SRR12071682, SRR11116086, SRR10451708, SRR10451725, SRR10536656, SRR10451709, SRR10536658, SRR10536659, SRR10536660, SRR10536661, SRR10536662, SRR10536663, SRR10451711, SRR10536665, SRR10536666, SRR10536667, SRR10536669, SRR10536670, SRR10536671, SRR10536672, SRR10536673, SRR10536674, SRR11536633, SRR11536634, SRR10451718, SRR10546708, SRR10559557, SRR11621679, SRR10600402, SRR11960525, SRR10600523, SRR10451720, SRR11960529, SRR10609374, SRR10609380, SRR10609382, SRR10609383, SRR10609386, SRR10609387, SRR10609388, SRR10609391, SRR10609392, SRR10609393, SRR10613301, SRR10613302, SRR11960626, SRR10947777, SRR10947785, SRR10451721, SRR10947787, SRR10948144, SRR10948120, SRR10948212, SRR10948217, SRR10948273, SRR10948361, SRR11960630, SRR10948365, SRR10948370, SRR10948371, SRR11960632, SRR10948364, SRR11039029, SRR11039030, SRR11059186, SRR11059188, SRR11059190, SRR11059192, SRR11059194, SRR11059196, SRR11067917, SRR11067918, SRR11067919, SRR11068074, SRR11068075, SRR11068076, SRR11068079, SRR11068080, SRR11068085, SRR11068086, SRR11068087, SRR11068088, SRR11068093, SRR11068159, SRR11091346, SRR11091347, SRR11091348, SRR11091349, SRR11091350, SRR11091351, SRR11091352, SRR11091353, SRR11091354, SRR11091355, SRR11091356, SRR11091357, SRR11091358, SRR11091359, SRR11091361, SRR11091364, SRR11113559, SRR11113562, SRR11113564, SRR11113565, SRR11113566, SRR11113567, SRR11113568, SRR11113569, SRR11113570, SRR11113571, SRR11113572, SRR11113573, SRR11113574, SRR11114574, SRR11114576, SRR11114577, SRR11114578, SRR11114579, SRR11114581, SRR11114627, SRR11114628, SRR11114629, SRR12643357, SRR11116073, SRR11116074, SRR11116076, SRR11116083, SRR11116084, SRR11116085, SRR11116104, SRR10959939, SRR11251334, SRR11116089, SRR11116090, SRR11116092, SRR11116072, SRR11116093, SRR11116094, SRR11116095, SRR11116096, SRR11116097, SRR11116098, SRR10451724, SRR11116100, SRR11116101, SRR11116087, SRR11251328, SRR11251336, SRR10600525, SRR10536657, SRR11187233, SRR11187234, SRR11187235, SRR11187236, SRR11187237, SRR11187239, SRR12071684, SRR11187241, SRR11230643, SRR11230717, SRR11230720, SRR11230721, SRR11230722, SRR11230723, SRR11230724, SRR11237628, SRR11251324, SRR11251325, SRR11251326, SRR11251327, SRR10536664, SRR11251329, SRR11251330, SRR11251331, SRR10537325, SRR10537328, SRR11116105, SRR11251335, SRR10537329, SRR10559569, SRR11251338, SRR11251365, SRR11251366, SRR11251367, SRR11251368, SRR11536630, SRR11536631, SRR11116099, SRR10600403, SRR11536635, SRR11536636, SRR11536637, SRR11617886, SRR11617968, SRR11618034, SRR11618040, SRR11621676, SRR11621678, SRR11251332, SRR11621680, SRR11116102, SRR11960526, SRR11960527, SRR11960528, SRR11251333, SRR11960530, SRR11960617, SRR11960618, SRR11960622, SRR11960624, SRR11960625, SRR10959938, SRR11960628, SRR11960635, SRR11960631, SRR12643358, SRR10948215, SRR12071681, SRR11116103, SRR12071683, SRR10600524, SRR12174400, SRR12174404, SRR12174406, SRR12424844, SRR12424848, SRR12424849, SRR12424850, SRR12424853, SRR12424854, SRR12424855, SRR12424857, SRR12424858, SRR12424859, SRR12424861, SRR12584068, SRR12584069, SRR12584070, SRR12584071, SRR12584072, SRR12584073, SRR12584074, SRR12584075, SRR12584076, SRR12584077, SRR12584078, SRR12584079, SRR12584080, SRR12584081, SRR12584082, SRR12584083, SRR12584084, SRR12584085, SRR12584086, SRR12584089, SRR12586812, SRR12586813, SRR12586814, SRR12586815, SRR12586816, SRR12586819, SRR12586820, SRR12586821, SRR12586822, SRR12586823, SRR12586824, SRR12643343, SRR12643346, SRR12643347, SRR12643349, SRR12643353, SRR12643354, SRR12643356, SRR11187232, SRR11187240, SRR12643360, SRR12643361, SRR12643365, SRR12643367, SRR12643368, SRR12643371, SRR12663939, SRR12663940, SRR12663941, SRR12663942, SRR12663943, SRR12663944, SRR12706037, SRR12706039, SRR12706040, SRR12706041, SRR12706042, SRR12777348, SRR12777350, SRR12777351, SRR12824293, SRR11068078, SRR10546709, and SRR11230719.

Selection of heavy metals of interest

Informed by a systematic literature review of HMRGs in E. coli, we selected five heavy metals of public health concern [4] with confirmed presence in the Salish Sea region [20, 21]: arsenic, cadmium, copper, lead, and mercury.

Screening of E. coli genomes for heavy metal resistance genes

We constructed a novel bioinformatic pipeline based on existing bioinformatic tools to analyze both HMRGs and ARGs.

Sequence retrieval, filtering, and assembly

First, the sequences were retrieved from the 308 isolates from the National Center for Biotechnology Information Sequence Read Archive (SRA) using SRA Toolkit [22] as FASTQ files. Then, the raw paired-end sequence data were filtered using Trimmomatic [23] with a sliding window trimming size of 4 bases and required average quality of 20, minimum read length of 25 bases, and removal of Illumina adapters with a maximum seed mismatch count of 2, palindrome clip threshold of 40, and simple clip threshold of 15. Next, genomes were assembled for each sample (contigs) using MEGAHIT with default settings [24]. The open reading frames were identified with Prodigal [25] for putative genes using default settings.

Screening for heavy metal resistance genes

Using the BacMet-Scan command line tool, we cross-referenced the translated proteins to the antibacterial biocide and metal resistance genes (BacMet) database [26] with a DIAMOND Basic Local Alignment Search Tool for Proteins (BLASTP) search to identify HMRGs for each sequence.

BacMet-Scan screens for a total of 171 HMRGs in its experimentally confirmed resistance gene database (version 2.0) [26]. We used the experimentally confirmed database from BacMet as opposed to the predicted resistance genes database to allow for comparison between the current study results and prior findings in the literature. Of 171 possible HMRGs in the BacMet database, we screened for HMRGS for five heavy metals (arsenic, cadmium, copper, lead, and mercury), which are often associated with mobile elements [27]. A total of 22 HMRGs were selected: arsenic (arsB, arsC, arsD, arsR), cadmium/mercury (dsbA, dsbB, robA), cadmium (ygiW, zinT/yodA), copper (bhsA/ycfR/comC, comR/ycfQ, cusR/ylcA, cusS, cutA, cutC, cutF/nlpE, dsbC, pcoA, pcoB, pcoC, pcoD). For our analyses, pcoA, pcoB, pcoC, and pcoD were consolidated to a singular HMRG (pcoABCD) since they are each required for the copper-inducible expression of copper resistance and part of the copper resistance determinant system [26].

There were 18 HMRGs on our final screening list: four functional arsenic resistance genes, three cadmium/mercury resistance genes, two cadmium genes, and nine copper genes. We used a 90% identity match threshold in the alignment between the best matching HMRG in BacMet and the corresponding sequence in the input genome and 100% minimum length (i.e., the alignment must cover the entire length of the HMRG in the database with no gap openings). There were no functional lead resistance genes that met our inclusion criteria.

Among the isolates collected from water sources, we additionally assessed if the occurrence of HMRGs varied by geographic location in the Salish Sea ecosystem.

Comparison to genotypic and phenotypic antibiotic resistance

We defined co-resistance as carriage of at least one HMRG and at least one ARG by an E. coli isolate. To explore genetic linkage between HMRGs and ARGs, we performed a sub-analysis on the 25 E. coli isolates that had previously been found to carry 1–4 ARGs [16]. Twenty-three were phenotypically antibiotic resistant and two isolates were tetracycline-intermediate resistant but carried known tet genes tet(A) or tet(B). We defined linkage as the physical location of a HMRG and an ARG next to one another in the same DNA sequence, whether chromosome or plasmid [28].

Among the 224 isolates from water sources, we assessed if the carriage of HMRGs differed by proximity to Superfund sites or geographic location. We used the Public Health Agency of Canada’s Staramr tool [29] to scan E. coli genome contigs against the Center for Genomic Epidemiology’s ResFinder (2022-05-24 update) [30–32] and PointFinder (2021-02-01 update) [33] databases using the default 90% identity match and 60% minimum length coverage (percent overlap) of the target gene thresholds (as suggested by the Center for Genomic Epidemiology [31]), as well as 100% minimum total length coverage to be comparable with past analyses of the isolates [16]. To identify plasmid sequences among the E. coli isolate genomes, we scanned contigs against PlasmidFinder (2021-11-29 update) (0.8.0.dev2) [34, 35] using the same criteria.

To determine if there were significant associations between carriage of ARGs and the HMRGs that were not carried by all isolates, we ran Pearson’s Chi-squared (two-sided) test with a Yates’ correction for continuity due to small numbers at the p<0.10 and p<0.05 levels.

Results

Carriage of heavy metal resistance genes

At least one HMRG of interest was detected in every study isolate. Each isolate carried a range of 14–20 copies of HMRGs of interest, with some isolates carrying multiple copies of the same gene (Table 1). Eleven (61%) of the 18 HMRGs screened were identified in all 308 isolates: arsC, bhsA/ycfR/comC, comR/ycfQ, cutA, cutC, cutF/nlpE, dsbA, dsbB, dsbC, robA, and ygiW (S1 Table). The copper resistance gene cutF/nlpE was the most prevalent HMRG in our data, identified 321 times, which included 10 isolates each carrying two copies of the gene and one isolate carrying four copies (Fig 1). A cadmium/mercury resistance gene, robA, was the second most prevalent HMRG (n = 311), also carried by all study isolates, with one isolate from a river otter in the Green River Natural Area carrying three copies. The third most prevalent HMRG (n = 310) was arsC, an arsenic resistance gene, with two isolates from water sources (South Salish Sea and Strait of Juan de Fuca) carrying two copies each.

Table 1. Count of selected heavy metal resistance genes (HMRGs) in 308 Escherichia coli isolates by Salish Sea region or source.

Isolate Source Arsenic Cadmium/Mercury Cadmium Copper Total HMRGs Countb
arsB a arsC arsD a arsR a dsbA dsbB robA ygiW zinT/yodA a bhsA/ycfR/comC comR/ycfQ cusR/ylcA a cusS a cutA cutC cutF/nlpE dsbC pcoABCD a
Water
North Salish Sea (n = 52) 45 52 2 44 52 52 52 52 52 52 52 52 52 52 52 56 52 0 823
Central Salish Sea (n = 55) 41 55 0 40 55 55 56 55 55 55 55 55 56 55 55 59 55 0 857
South Salish Sea (n = 57) 46 58 3 46 58 57 57 57 54 57 57 56 56 57 57 58 58 0 892
Strait of Juan de Fuca (n = 52) 38 53 3 38 52 52 52 52 52 52 52 51 52 52 52 53 52 1 809
Fresh Water (n = 5) 3 5 0 3 5 5 5 5 5 5 5 5 5 5 5 5 5 0 76
Marine Water by Beaches (n = 3) 3 3 0 3 3 3 3 3 3 3 3 3 3 3 3 3 3 0 48
Marine Mammals
Harbor Seals (n = 51) 31 51 1 31 51 52 51 51 51 51 51 51 51 51 51 53 51 3 783
Harbor Porpoises (n = 7) 3 7 0 3 7 7 7 7 7 7 7 7 7 7 7 7 7 0 104
River Otters (n = 24) 23 24 2 22 24 24 26 24 24 24 24 24 24 25 24 25 24 3 390
Sole (n = 2) 2 2 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 32
Total (N = 308) 235 310 11 232 309 309 311 308 305 308 308 306 308 309 308 321 309 7 —
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aThis HMRG was not found in every study isolate and was only carried by some isolates. arsB was carried by 231 isolates; arsD was carried by 11 isolates; arsR was carried by 230 isolates; zinT/yodA was carried by 305 isolates; cusR/ylcA was carried by 306 isolates; cusS was carried by 306 isolates; and pcoABCD was carried by 7 isolates.

bIf the count for a HMRG is 3 in the table, it means that there are 3 of the same HMRG identified in isolates from a given source (e.g., South Salish Sea).

Fig 1. Total count of heavy metal resistance genes per E. coli isolate source (N = 308).

Fig 1

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Number of isolates per source: North Puget Sound (n = 52), Central Puget Sound (n = 55), South Puget Sound (n = 57), Strait of Juan de Fuca (n = 52), Fresh Water (n = 5), Marine Water by Beaches (n = 3), Harbor Seal (n = 51), Harbor Porpoise (n = 7), River Otter (n = 24), Sole (n = 2).

In contrast, the copper resistance gene pcoABCD was identified only seven times in the samples, primarily in E. coli isolates from mammals (river otters and harbor seals), and one isolate from water. We found an association between the presence of this gene and the presence of certain ARGs. Specifically, six ARGs were found to be significantly associated with pcoABCD at the p<0.10 level: aac(3)-IV, aph(3’)-Ia, aph(4)-Ia, aph(6)-Id, lnu(F), and tet(B); however, the isolates carrying the aminoglycoside genes were previously shown not to be phenotypically resistant [16] (S2 Table). An arsenic gene, arsD, was identified in 73% (n = 11) of the isolates from the South Salish Sea, Strait of Juan de Fuca, and North Salish Sea, with two isolates from river otters in Hamm Creek and one isolate from a harbor seal in Fort Flagler Historical State Park. The fluoroquinolone resistance gene qnrB82, carried by only one out of 25 isolates, was found to be significantly associated with arsD at the p<0.05 level, though the isolate was not ciprofloxacin-resistant [16]. No other HMRG-ARG associations were statistically significant.

Geographic variation of heavy metal resistance genes in isolates from water sources

Of the 18 HMRGs that we screened, only seven HMRGs were not universally found in all study isolates: arsB, arsD, arsR, zinT/yodA, cusR/ylcA, cusS, and pcoABCD. Nearly all (≥95%) of the isolates from water sources carried copies of zinT/yodA, cusR/ylcA, and cusS (Table 2). In contrast, carriage of arsD and pcoABCD were uncommon in our study isolates (8/224 or 3.6% and 1/224 or 0.4%, respectively).

Table 2. Number of non-universal heavy metal resistance genes (HMRGs) carried by Escherichia coli isolates of water sources in the Salish Sea (N = 224).

Salish Sea Quadrant Arsenic Cadmium Copper Total Isolates Per Region
arsB arsD arsR zinT/yodA cusR/ylcA cusS pcoABCD
n (%)
North Salish Sea 44 (85) 2 (4) 44 (85) 52 (100) 52 (100) 52 (100) 0 (0) 52
Central Salish Sea 40 (73) 0 (0) 40 (73) 55 (100) 55 (100) 55 (100) 0 (0) 55
 Fresh Water 3 (60) 0 (0) 3 (60) 5 (100) 5 (100) 5 (100) 0 (0) 5
 Marine Water by Beaches 3 (100) 0 (0) 3 (100) 3 (100) 3 (100) 3 (100) 0 (0) 3
South Salish Sea 46 (81) 3 (5) 46 (81) 54 (95) 56 (98) 56 (98) 0 (0) 57
Strait of Juan de Fuca 37 (71) 3 (6) 37 (71) 52 (100) 51 (98) 51 (98) 1 (2) 52
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Seven HMRGs were not ubiquitous in terms of their distribution across four quadrants of the Salish Sea (North Salish Sea; Central Salish Sea, with samples from the fresh water and marine water by beaches; South Salish Sea; and Strait of Juan de Fuca). Of the seven non-universally found HMRGs, arsB and arsR were the most prevalent among the isolates from water samples in the four different quadrants, with 100% of these isolates carrying both genes. We additionally compared the HMRGs carried by isolates also carrying expressed ARGs (n = 25) with those carried by isolates without ARGs (n = 276; S1 File).

Fifteen percent (n = 45) of the E. coli isolates in the study were from sources located near (i.e., directly within or geographically adjacent to) Superfund sites currently on the US Environmental Protection Agency’s National Priorities List. Of those 45 isolates, there were seven isolates from water samples in the Central Salish Sea near the Naval Undersea Warfare Engineering Station, Puget Sound Naval Shipyard, and Old Navy Dump/Manchester Laboratory Superfund sites (S1 Table). These seven isolates did not carry more total copies of HMRGs (range per isolate: 14–17) than the other 48 isolates collected from non-Superfund adjacent locations in the Central Salish Sea (range: 14–17). None of the isolates from water samples collected in the North Salish Sea, South Salish Sea, Strait of Juan de Fuca, fresh water, or marine water by beaches were near Superfund sites on the National Priorities List, however, all exhibited universal carriage of HMRGs (range: 14–20).

Carriage of plasmids

Overall, 173 (56%) of the study isolates carried plasmid sequences. Out of 25 isolates with phenotypic resistance to antibiotics and carriage of at least one ARG, 20 (80%) also carried at least one plasmid sequence. Of the 283 isolates with no ARGs detected by WGS, 152 (54%) carried plasmid sequences (S3 Table). Four of these isolates (CWG7G, CWG7H, GRNRA4F, and 342381-006-850) were phenotypically resistant to antibiotics and carried plasmid sequences, but no ARGs were detected by WGS (S3 Table) [16].

Antibiotic resistance genes, heavy metal resistance genes, plasmids, and Superfund sites

The 25 isolates that carried ARGs and that were phenotypically non-susceptible (resistant or intermediate susceptible) to antibiotics included two isolates from the Central Salish Sea, three isolates from fresh water, eight isolates from harbor seals, four isolates from the North Salish Sea, and eight isolates from river otters (Table 2). Overall, the most common ARGs reported were tet(B) and aph(6)-Id (Fig 2 and S1 Fig). We observed that 40% (n = 10) of these non-susceptible isolates had HMRGs and non-functional ARGs that were located next to each other and assumed to be linked on their assembled genomes (chromosome or plasmid sequences).

Fig 2. Total count of antibiotic resistance genes per E. coli isolate source (N = 308).

Fig 2

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Number of isolates per source: North Puget Sound (n = 52), Central Puget Sound (n = 55), South Puget Sound (n = 57), Strait of Juan de Fuca (n = 52), Fresh Water (n = 5), Marine Water by Beaches (n = 3), Harbor Seal (n = 51), Harbor Porpoise (n = 7), River Otter (n = 24), Sole (n = 2).

Among the subset of isolates with phenotypic resistance (n = 25), the ARGs catA1 and sul2 were found with the HMRG cusS, both located on the IncQ1 plasmid sequence in two harbor seal isolates, suggesting potential co-selection for catA1, sul2, and cusS resistance genes on the IncQ1 plasmid (using 90% identity match and 60% minimum length thresholds). IncQ1 plasmids have been shown to carry sul2, strAB, and tet(A) genes [36]. In our study, though found in both water and animal isolates, sul2 was carried primarily in isolates from marine mammals (five harbor seals and one river otter). Further, we found that sul2 was linked with HMRGs in three of the marine mammals isolates and one North Salish Sea water isolate.

E. coli isolates from water sources

In the two isolates taken from water samples in Drayton Harbor, North Salish Sea (339942-001-501 and 339942-002-506), the position of the tet(A) gene was linked with all identified HMRGs except for bhsA/ycfR/comC, a copper resistance gene (Table 2). Further, in both of those isolates, the qnrB19 ARG was linked with arsenic and copper resistance genes (arsB and cusS, respectively), in the chromosome. While both isolates carried the IncX1 plasmid sequence, and the isolate 339942-002-506 also carried the IncFIB(AP001918) plasmid sequence and demonstrated intermediate phenotypic resistance to ciprofloxacin, no ARGs or HMRGs were located on the plasmid sequences in either isolate. Additional findings of E. coli isolates from water sources are reported in the S1 File.

E. coli isolates from marine mammal sources

Among the eight phenotypically antibiotic-resistant E. coli isolated from harbor seals, the most common ARG-HMRG combinations consisted of the sul2 gene and the following 14 HMRGs: arsC, bhsA/ycfR/comC, comR/ycfQ, cusR/ylcA, cusS, cutA, cutC, cutF/nlpE, dsbA, dsbB, dsbC, robA, ygiW, and zinT/yodA. The sul2 gene is often associated with integrons (S2 Fig). Three of the isolates from harbor seals were phenotypically resistant to doxycycline and three were phenotypically resistant to trimethoprim/sulfamethoxazole. One harbor seal (EPA Dock G Cip 1#5) carried aph(3")-Ib, aph(6)-Id, catA1, floR, sul2, and tet(A) ARGs, one copy of each HMRG except for arsD and pcoABCD, and was phenotypically resistant to ciprofloxacin, levofloxacin, and tetracycline. For the isolate EPA Dock G Cip 1#5, the positions of the catA1 and sul2 genes were upstream from the position of the cusS copper resistance gene and was associated with the IncQ1 plasmid sequence. For one of the isolates taken from a harbor seal in Seattle (SKMMR2020-01-025 Fecal #1), the positions of the catA1 and sul2 ARGs were located upstream of the cusS copper resistance gene and associated with the IncQ1 plasmid.

Among the eight E. coli isolates from river otters, all carried 14–17 HMRGs. The most common ARG-HMRG combination was between tet(B) and cutF/nlpE, which occurred in five (62%) of those isolates (project IDs: BR1E, BR1F, CWG3I, HAM5E, HAM6D) (S3 Fig). In an isolate from a river otter in Hamm Creek (HAM5E), the positions of ARGs qnrB19, aph(6)-Id, and catA1 overlapped with the position of nine HMRGs (arsB, comR/ycfQ, cusS, cutC, cutF/nlpE, dsbA, dsbC, robA, zinT/yodA) and were physically located on the same Col(pHAD28) plasmid sequence. The isolate HAM5E was phenotypically resistant to ampicillin, trimethoprim/sulfamethoxazole, tetracycline, minocycline, and sulfisoxazole. Additional results are reported in the S1 File.

Discussion

This study found high carriage rates of HMRGs for arsenic, cadmium, copper, and mercury in all genomes of E. coli isolates collected from the Salish Sea marine environment. Among the isolates with phenotypic resistance to antibiotics as well as ARGs, we identified linkage between HMRGs and ARGs. While only a few of the isolates in the study had HMRGs and ARGs linked to plasmid sequences, there was greater prevalence of plasmid sequences among ARG-carrying isolates than among non-ARG carrying isolates. Finally, we did not find measurable differences in the total number of HMRG copies carried by isolates from water sources according to geographic location or proximity to known Superfund sites.

Overall, there was a high prevalence of HMRGs across arsenic, cadmium, copper, and mercury functional resistance genes observed in our study isolates, suggesting prominent and universal exposure to heavy metals in the environment and among marine mammals in the Salish Sea. The most prevalent HMRGs identified in the isolates were a copper resistance gene cutF/nlpE, a cadmium/mercury resistance gene robA, and an arsenic resistance gene arsC.

In general, there was a high prevalence of copper resistance genes in E. coli isolates from the various water sources and marine mammals. The copper homeostasis protein encoded by cutF could be involved in both copper efflux and the delivery of copper to copper-dependent enzymes [26]. When overproduced, the cutF/nlpE gene product induces DegP, which acts as a protease in the acid resistance of E. coli [37] and is required for bacterial survival in harsh environmental conditions, including high temperatures [38]. Our finding of copper resistance genes in E. coli isolated throughout the Salish Sea ecosystem suggests widespread bacterial exposure to copper that should be further investigated.

The second most prevalent HMRG we identified was the robA gene, encoding a transcriptional activator that confers bacterial resistance to both cadmium and mercury resistance [26]. When overexpressed, the robA gene product induces multiple antibiotic and heavy metal resistance traits, as well as organic solvent tolerance in E. coli [39, 40]. In our study, five isolates that carried robA were phenotypically resistant to tetracycline, one was phenotypically resistant to chloramphenicol, and one intermediate-susceptible to kanamycin.

The third most prevalent HMRG found was an arsenic resistance gene, arsC, with the function of reducing arsenate to the more-toxic arsenite [26]. Having multiple copies of the ars operon increases resistance to arsenate. Prior studies have shown the widespread prevalence of arsC genes in water sources globally [15, 41, 42], suggesting high levels of arsenic pollution in the environment. Researchers have recommended bacteria carrying arsC as a potential bioremediation strategy in areas heavily contaminated with arsenic [43]. Examining the isolates from water sources only, arsB and arsR were the most prevalent HMRGs—a finding which is consistent with a recent study of Staphylococcus aureus in macaques, which found arsB and arsR in all study strains [44].

In a subset of 25 isolates that were previously found to be resistant to antibiotics [16], we observed overall high rates of co-resistance of HMRG and ARGs, and even genetic linkage of certain HMRGs and ARGs in a minority of isolates. The resistome (i.e., collection of all ARGs) [45] in the environment has expanded due to resistant organisms in human and environmental waste entering the environment without adequate treatment, in addition to the possibility of antibiotic residues and heavy metal pollution. E. coli isolates from human, animal, and environmental sources globally have revealed the diversity of ARGs from the same geographical reservoir that can be accumulated, carried, and transferred [16, 46, 47]. Further, previous work has shown linkages between selection for ARGs and HMRGs, specifically through co-occurrence [1] and cross-selection, in livestock [12, 13, 48], sediments [49], soils [50–52], wastewater treatment plants [53, 54], and in various water sources [15, 55–57]. The interactions of human, animal, and environmental factors in bacterial antimicrobial resistance call for an integrated approach to understanding transmission and evolution of heavy metals and antimicrobial resistance.

Due to their remarkable capacity to carry aggregates of ARGs, HMRGs, and virulence factors, plasmids spread drug resistance throughout bacterial populations via transduction or conjugation [27]. Plasmids may play a potentially important role in the movement of resistance genes in the Salish Sea ecosystem: more than half of the sequences in our study carried both HMRGs and plasmids, and a greater proportion of the isolates carrying ARGs carried plasmids compared to isolates without ARGs. The sul2 gene is often associated with small nonconjugative plasmids [58] or on large transmissible multi-resistance plasmids [59], such as the IncQ1 plasmid. While the acquisition of multiple sulfonamide resistance genes has been reported previously [60], in our study, we only had one isolate (from Portage Bay) that carried copies of both sul1 and sul2 genes, and only the sul2 and catA1 genes were located on the IncQ1 plasmid. A study of E. coli isolates from domestic animals and children identified carriage of both the catA1 gene and the IncQ1 plasmid in the same isolate, however, the association of catA1 with IncQ1 was not specifically examined [61]. Although we identified potential linkage for catA1, sul2, and cusS resistance genes on the IncQ1 plasmid for two harbor seal isolates in our study, no other studies have, to our knowledge, found cusS to be located with IncQ1.

While there is a history of hazardous waste pollution in the Salish Sea, we did not observe differences in carriage of HMRGs in E. coli isolates by proximity to Superfund sites. Further, we found that HMRGs were more common than ARGs in E. coli isolates, suggesting that exposures to heavy metals may be greater than exposure to antibiotics in this ecosystem. This may be because unlike antibiotics, heavy metals are stable and cannot be eliminated easily from the environment [62]. Thus, they persist in the environment much longer than do active antibiotics or residues that can select for ARG resistance. For example, the efficacy of antibiotics wanes with increased ultraviolet light/sunlight exposure [63], but due to the ability of most metals to absorb photon energy with free electrons available, they will not break down when directly exposed to ultraviolet light [64]. Therefore, knowing that Superfund sites polluted hazardous waste containing heavy metals (including arsenic, cadmium, copper, and mercury) into the Salish Sea ecosystem in the past, it is not entirely surprising that we did not observe differences in HMRG carriage by proximity to Superfund sites; HMRGs may have spread throughout the Salish Sea’s catchment area over the decades since the Superfund sites began their cleanup processes.

Since all study isolates carried HMRGs, a limitation of this study was the lack of a comparison group of genomes without HMRGs. The cross-sectional nature of the study precluded determination of the temporal relationship of the observed associations (e.g., did HMRG acquisition precede or follow ARG acquisition?), limiting any conclusions about causality. Similarly, we did not have access to exposure data (such as heavy metal measurements) from the environments where the samples were taken, and our reliance on proxy indicators (e.g., existence of a nearby Superfund site) may have resulted in misclassification of exposures, resulting in a bias toward the null hypothesis. Additionally, our sample contained only E. coli from animal and water sources, though it is possible that different HMRG patterns could be seen in isolates from human sources (which are the best characterized isolates). There was varying correlation between antibiotic resistance phenotype and carriage of corresponding known resistance genes, with 100% of tet-resistant/intermediate isolates carrying tet genes, but low correlation between aminoglycoside resistance phenotypes and genotypes. We also did not test for phenotypic heavy metal resistance; therefore, it is not clear whether the presence of HMRGs conferred actual resistance to their host E. coli. Lastly, the list of HMRGs we screened for was based on four heavy metals of public health relevance and was not an exhaustive screening of all HMRGs that could exist in the study samples. Genes conferring resistance to lead, often the most prevalent heavy metal contaminant in environments [2], were not found in our study. While the literature on heavy metal resistance is growing, characterization of HMRGs in bacteria as markers for public health risk from heavy metal exposure has not been extensively explored recently.

The strengths of our study include the novel screening for HMRGs in E. coli genomes isolated from various sources in the Salish Sea ecosystem, adding to the characterization of potential health impacts of Superfund sites on nearby communities/ecosystems, using the environment and animals as sentinels for human health, utilization of a diversity of sample types (water and marine mammals), having a relatively large total sample size, and having exact base pair positions in the genome to determine linkage of ARGs and HMRGs.

Our study and past literature demonstrate evidence of widespread heavy metal resistance in E. coli isolates. The co-resistance of arsenic, cadmium, copper, and mercury-resistance genes with a diversity of resistance genes to commonly used antibiotics identified in our study have important potential implications for clinical applications. As E. coli continues to cycle through communities and the post-antibiotic era approaches, it is crucial to conduct global surveillance on the different resistance genes that E. coli isolates carry to recognize the limitations to future antibiotic efficacy. More specifically, understanding the specific genes that are present in the co-resistance of antibiotics and heavy metals in different reservoirs can help public health practitioners better predict what resistance patterns to expect in the future. Further, human, animal, and ecosystem aspects of AMR should be viewed in an integrative manner [65] that reflects the common environmental habitats and stressors of animals and humans through which resistance genes can be spread. Just as animals can serve as sentinels for human health, HMRGs surveillance may serve to estimate the nature and extent of heavy metal pollution in a given environment.

Supporting information

S1 Table. Total count of selected heavy metal resistance genes (arsenic, cadmium, copper, and mercury) in study isolates by Salish Sea region and source (N = 308).

(DOCX)

Click here for additional data file. (182.2KB, docx)
S2 Table. Co-resistance and linkage of heavy metal resistance genes (HMRGs), antibiotic resistance genes (ARGs), and plasmids in E. coli isolates by Salish Sea region and isolate sampling source (N = 25).

(DOCX)

Click here for additional data file. (91.5KB, docx)
S3 Table. Output from the Staramr tool with study E. coli genome contigs scanned against the Center for Genomic Epidemiology’s ResFinder, PointFinder, and PlasmidFinder databases using the default 90% identity match and 60% minimum length coverage of the target gene thresholds, and 100% minimum total length coverage.

(XLSX)

Click here for additional data file. (32.3KB, xlsx)
S1 Fig. Total count of antibiotic resistance genes per E. coli isolate (N = 25).

(TIF)

Click here for additional data file. (958.1KB, tif)
S2 Fig. Total counts of heavy metal resistance genes and antibiotic resistance genes in E. coli isolates, harbor seals (N = 8).

(TIF)

Click here for additional data file. (1.1MB, tif)
S3 Fig. Total counts of heavy metal resistance genes and antibiotic resistance genes in E. coli isolates, river otters (N = 8).

(TIF)

Click here for additional data file. (1.1MB, tif)
S1 File. Supplementary results.

(DOCX)

Click here for additional data file. (32.5KB, docx)

Acknowledgments

We would like to thank Pauline Trinh, Evan Pepper, and David No for their bioinformatics assistance, Brian High for his coding help, Lauren Frisbie and Alexandria Vingino for their prior work on the study, and Cheryl Adler, Stephanie Norman, and Erica Fuhrmeister for their subject matter expertise regarding the manuscript.

Data Availability

All sequence data are available from the U.S. National Institutes of Health National Center for Biotechnology Information (NCBI) BioProject database (BioProject accession number PRJNA283914). The NCBI Sequence Read Archive IDs for the 308 included isolates were: SRR11116088, SRR10947731, SRR10451710, SRR11116091, SRR10451712, SRR10451715, SRR10451717, SRR11251337, SRR10451719, SRR12071682, SRR11116086, SRR10451708, SRR10451725, SRR10536656, SRR10451709, SRR10536658, SRR10536659, SRR10536660, SRR10536661, SRR10536662, SRR10536663, SRR10451711, SRR10536665, SRR10536666, SRR10536667, SRR10536669, SRR10536670, SRR10536671, SRR10536672, SRR10536673, SRR10536674, SRR11536633, SRR11536634, SRR10451718, SRR10546708, SRR10559557, SRR11621679, SRR10600402, SRR11960525, SRR10600523, SRR10451720, SRR11960529, SRR10609374, SRR10609380, SRR10609382, SRR10609383, SRR10609386, SRR10609387, SRR10609388, SRR10609391, SRR10609392, SRR10609393, SRR10613301, SRR10613302, SRR11960626, SRR10947777, SRR10947785, SRR10451721, SRR10947787, SRR10948144, SRR10948120, SRR10948212, SRR10948217, SRR10948273, SRR10948361, SRR11960630, SRR10948365, SRR10948370, SRR10948371, SRR11960632, SRR10948364, SRR11039029, SRR11039030, SRR11059186, SRR11059188, SRR11059190, SRR11059192, SRR11059194, SRR11059196, SRR11067917, SRR11067918, SRR11067919, SRR11068074, SRR11068075, SRR11068076, SRR11068079, SRR11068080, SRR11068085, SRR11068086, SRR11068087, SRR11068088, SRR11068093, SRR11068159, SRR11091346, SRR11091347, SRR11091348, SRR11091349, SRR11091350, SRR11091351, SRR11091352, SRR11091353, SRR11091354, SRR11091355, SRR11091356, SRR11091357, SRR11091358, SRR11091359, SRR11091361, SRR11091364, SRR11113559, SRR11113562, SRR11113564, SRR11113565, SRR11113566, SRR11113567, SRR11113568, SRR11113569, SRR11113570, SRR11113571, SRR11113572, SRR11113573, SRR11113574, SRR11114574, SRR11114576, SRR11114577, SRR11114578, SRR11114579, SRR11114581, SRR11114627, SRR11114628, SRR11114629, SRR12643357, SRR11116073, SRR11116074, SRR11116076, SRR11116083, SRR11116084, SRR11116085, SRR11116104, SRR10959939, SRR11251334, SRR11116089, SRR11116090, SRR11116092, SRR11116072, SRR11116093, SRR11116094, SRR11116095, SRR11116096, SRR11116097, SRR11116098, SRR10451724, SRR11116100, SRR11116101, SRR11116087, SRR11251328, SRR11251336, SRR10600525, SRR10536657, SRR11187233, SRR11187234, SRR11187235, SRR11187236, SRR11187237, SRR11187239, SRR12071684, SRR11187241, SRR11230643, SRR11230717, SRR11230720, SRR11230721, SRR11230722, SRR11230723, SRR11230724, SRR11237628, SRR11251324, SRR11251325, SRR11251326, SRR11251327, SRR10536664, SRR11251329, SRR11251330, SRR11251331, SRR10537325, SRR10537328, SRR11116105, SRR11251335, SRR10537329, SRR10559569, SRR11251338, SRR11251365, SRR11251366, SRR11251367, SRR11251368, SRR11536630, SRR11536631, SRR11116099, SRR10600403, SRR11536635, SRR11536636, SRR11536637, SRR11617886, SRR11617968, SRR11618034, SRR11618040, SRR11621676, SRR11621678, SRR11251332, SRR11621680, SRR11116102, SRR11960526, SRR11960527, SRR11960528, SRR11251333, SRR11960530, SRR11960617, SRR11960618, SRR11960622, SRR11960624, SRR11960625, SRR10959938, SRR11960628, SRR11960635, SRR11960631, SRR12643358, SRR10948215, SRR12071681, SRR11116103, SRR12071683, SRR10600524, SRR12174400, SRR12174404, SRR12174406, SRR12424844, SRR12424848, SRR12424849, SRR12424850, SRR12424853, SRR12424854, SRR12424855, SRR12424857, SRR12424858, SRR12424859, SRR12424861, SRR12584068, SRR12584069, SRR12584070, SRR12584071, SRR12584072, SRR12584073, SRR12584074, SRR12584075, SRR12584076, SRR12584077, SRR12584078, SRR12584079, SRR12584080, SRR12584081, SRR12584082, SRR12584083, SRR12584084, SRR12584085, SRR12584086, SRR12584089, SRR12586812, SRR12586813, SRR12586814, SRR12586815, SRR12586816, SRR12586819, SRR12586820, SRR12586821, SRR12586822, SRR12586823, SRR12586824, SRR12643343, SRR12643346, SRR12643347, SRR12643349, SRR12643353, SRR12643354, SRR12643356, SRR11187232, SRR11187240, SRR12643360, SRR12643361, SRR12643365, SRR12643367, SRR12643368, SRR12643371, SRR12663939, SRR12663940, SRR12663941, SRR12663942, SRR12663943, SRR12663944, SRR12706037, SRR12706039, SRR12706040, SRR12706041, SRR12706042, SRR12777348, SRR12777350, SRR12777351, SRR12824293, SRR11068078, SRR10546709, and SRR11230719.

Funding Statement

This work was supported by the National Institute of Environmental Health Sciences at the National Institutes of Health (https://www.niehs.nih.gov/), grant number T32 ES015459 to A.S.T. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Ayman Elbehiry

19 Sep 2023

PONE-D-23-17575Carriage of arsenic, cadmium, copper, and mercury heavy metal resistance genes in Escherichia coli isolates from a marine ecosystem with a history of environmental pollutionPLOS ONE

Dear Dr. Rabinowitz,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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PLOS ONE

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Comments to the Author

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The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: Yes

**********

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Reviewer #1: No

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #1: Peer review comments for minor revisions

The manuscript is based on impressive empirical evidence and makes an original contribution. Only minor revisions are needed before it can be published.

1. The authors conduct very relevant research, but unable to emphasis the relevance in the introduction.

2. To improve the readability of the paper, I suggest dividing the analysis into several subsections.

3. Table 2 is too long and difficult to understand, it should be adjusted.

4. Quality of figures should be improved, Text is very blurred and it is difficult to read black letters on dark green background.

5. There should be one more section conclusion/summary and future prospective to better reflect their work.

6. Line no. 23 page no. 2- sentence should be read as "We screened 18 functional . .

7. Line no. 24 page no. 2 sentence should be followed as "geographical variations . .

Reviewer #2: Comments to authors:

The current study is very interesting; however, the authors should address the following comments to improve the quality of the manuscript and to make it looks more beneficial to human health :

1- Title:

Please modify the title: All heavy metals mentioned in the title can be written between brackets in the end of the title, example: “study of heavy metal resistance genes in Escherichia coli isolates from a marine ecosystem with a history of environmental pollution, focusing on (arsenic, cadmium, copper, and mercury)”

2- Abstract:

- Rephrase the main conclusion of your findings to sound better.

3- Introduction: (it needs to be more informative), try to provide some information about the relationship between the effects of heavy metals in E.Coli and human health.

- Give a hint and some details about the spread of ARGs among and between humans and animals sources of HMRGs in bacterial environmental reservoirs.

- The authors should illustrate the importance of the study with regard to public health linked to the study objectives.

- Authors could add some paragraphs to fulfill the following gabs:

1- The relationship between the use of some metals as antibiotics for human treatment and antimicrobial resistance, heavy metal exposure, and resistance.

-Rephrase the aim of the work to be clear and better sound.

2- Write some paragraphs about Escherichia coli.

3- Material and methods

- R-write the methodology according to the PLOs guidelines.

-The Ethical statement should be placed before the sampling section since there samples taken from animals marine mammals (harbor seals, harbor porpoises, river otters).

-Isolation techniques analysis of samples isolates, should be modified.

- Methods of fecal samples collection and laboratory tests should be clearly described.

- Methods for isolating genes must be written, even if they are performed by contracting with a laboratory not associated with the study, regardless of its reliability or reputation

-Results:

- Increase the resolution of the two figures to be 600 dpi.

- Place Fig 1. “Total count of heavy metal resistance genes per E. coli isolate” and Fig.2 “Total count of antibiotic resistance genes per E. coli isolate source “ in their right place (not in the appendix)

- The manuscript is written well but needs minor revision for the grammatical errors and spelling mistakes.

- Please revise the references with the correct style of the journal.

**********

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Reviewer #1: Yes: Dr. Muhammad Abaid Ullah, DMMG, BZU, Multan, Pakistan

Reviewer #2: Yes: Dr Mustafa Mohammed Mustafa

**********

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PLoS One. 2023 Nov 16;18(11):e0294565. doi: 10.1371/journal.pone.0294565.r002

Author response to Decision Letter 0

1 Nov 2023

Thank you for your review of our manuscript and the thoughtful comments. In line with your comments, we have revised the manuscript for greater clarity, readability, and phrasing in certain sections. Please refer to the "Response to Reviewers" document for detailed responses to your comments.

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Decision Letter 1

Ayman Elbehiry

5 Nov 2023

Study of heavy metal resistance genes in Escherichia coli isolates from a marine ecosystem with a history of environmental pollution (arsenic, cadmium, copper, and mercury)

PONE-D-23-17575R1

Dear Dr. Peter Rabinowitz,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Ayman Elbehiry

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Ayman Elbehiry

9 Nov 2023

PONE-D-23-17575R1

Study of heavy metal resistance genes in Escherichia coli isolates from a marine ecosystem with a history of environmental pollution (arsenic, cadmium, copper, and mercury)

Dear Dr. Rabinowitz:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Professor Ayman Elbehiry

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Total count of selected heavy metal resistance genes (arsenic, cadmium, copper, and mercury) in study isolates by Salish Sea region and source (N = 308).

    (DOCX)

    Click here for additional data file. (182.2KB, docx)
    S2 Table. Co-resistance and linkage of heavy metal resistance genes (HMRGs), antibiotic resistance genes (ARGs), and plasmids in E. coli isolates by Salish Sea region and isolate sampling source (N = 25).

    (DOCX)

    Click here for additional data file. (91.5KB, docx)
    S3 Table. Output from the Staramr tool with study E. coli genome contigs scanned against the Center for Genomic Epidemiology’s ResFinder, PointFinder, and PlasmidFinder databases using the default 90% identity match and 60% minimum length coverage of the target gene thresholds, and 100% minimum total length coverage.

    (XLSX)

    Click here for additional data file. (32.3KB, xlsx)
    S1 Fig. Total count of antibiotic resistance genes per E. coli isolate (N = 25).

    (TIF)

    Click here for additional data file. (958.1KB, tif)
    S2 Fig. Total counts of heavy metal resistance genes and antibiotic resistance genes in E. coli isolates, harbor seals (N = 8).

    (TIF)

    Click here for additional data file. (1.1MB, tif)
    S3 Fig. Total counts of heavy metal resistance genes and antibiotic resistance genes in E. coli isolates, river otters (N = 8).

    (TIF)

    Click here for additional data file. (1.1MB, tif)
    S1 File. Supplementary results.

    (DOCX)

    Click here for additional data file. (32.5KB, docx)
    Attachment

    Submitted filename: Comments to authors.docx

    Click here for additional data file. (14.9KB, docx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (37.6KB, docx)

    Data Availability Statement

    All sequence data are available from the U.S. National Institutes of Health National Center for Biotechnology Information (NCBI) BioProject database (BioProject accession number PRJNA283914). The NCBI Sequence Read Archive IDs for the 308 included isolates were: SRR11116088, SRR10947731, SRR10451710, SRR11116091, SRR10451712, SRR10451715, SRR10451717, SRR11251337, SRR10451719, SRR12071682, SRR11116086, SRR10451708, SRR10451725, SRR10536656, SRR10451709, SRR10536658, SRR10536659, SRR10536660, SRR10536661, SRR10536662, SRR10536663, SRR10451711, SRR10536665, SRR10536666, SRR10536667, SRR10536669, SRR10536670, SRR10536671, SRR10536672, SRR10536673, SRR10536674, SRR11536633, SRR11536634, SRR10451718, SRR10546708, SRR10559557, SRR11621679, SRR10600402, SRR11960525, SRR10600523, SRR10451720, SRR11960529, SRR10609374, SRR10609380, SRR10609382, SRR10609383, SRR10609386, SRR10609387, SRR10609388, SRR10609391, SRR10609392, SRR10609393, SRR10613301, SRR10613302, SRR11960626, SRR10947777, SRR10947785, SRR10451721, SRR10947787, SRR10948144, SRR10948120, SRR10948212, SRR10948217, SRR10948273, SRR10948361, SRR11960630, SRR10948365, SRR10948370, SRR10948371, SRR11960632, SRR10948364, SRR11039029, SRR11039030, SRR11059186, SRR11059188, SRR11059190, SRR11059192, SRR11059194, SRR11059196, SRR11067917, SRR11067918, SRR11067919, SRR11068074, SRR11068075, SRR11068076, SRR11068079, SRR11068080, SRR11068085, SRR11068086, SRR11068087, SRR11068088, SRR11068093, SRR11068159, SRR11091346, SRR11091347, SRR11091348, SRR11091349, SRR11091350, SRR11091351, SRR11091352, SRR11091353, SRR11091354, SRR11091355, SRR11091356, SRR11091357, SRR11091358, SRR11091359, SRR11091361, SRR11091364, SRR11113559, SRR11113562, SRR11113564, SRR11113565, SRR11113566, SRR11113567, SRR11113568, SRR11113569, SRR11113570, SRR11113571, SRR11113572, SRR11113573, SRR11113574, SRR11114574, SRR11114576, SRR11114577, SRR11114578, SRR11114579, SRR11114581, SRR11114627, SRR11114628, SRR11114629, SRR12643357, SRR11116073, SRR11116074, SRR11116076, SRR11116083, SRR11116084, SRR11116085, SRR11116104, SRR10959939, SRR11251334, SRR11116089, SRR11116090, SRR11116092, SRR11116072, SRR11116093, SRR11116094, SRR11116095, SRR11116096, SRR11116097, SRR11116098, SRR10451724, SRR11116100, SRR11116101, SRR11116087, SRR11251328, SRR11251336, SRR10600525, SRR10536657, SRR11187233, SRR11187234, SRR11187235, SRR11187236, SRR11187237, SRR11187239, SRR12071684, SRR11187241, SRR11230643, SRR11230717, SRR11230720, SRR11230721, SRR11230722, SRR11230723, SRR11230724, SRR11237628, SRR11251324, SRR11251325, SRR11251326, SRR11251327, SRR10536664, SRR11251329, SRR11251330, SRR11251331, SRR10537325, SRR10537328, SRR11116105, SRR11251335, SRR10537329, SRR10559569, SRR11251338, SRR11251365, SRR11251366, SRR11251367, SRR11251368, SRR11536630, SRR11536631, SRR11116099, SRR10600403, SRR11536635, SRR11536636, SRR11536637, SRR11617886, SRR11617968, SRR11618034, SRR11618040, SRR11621676, SRR11621678, SRR11251332, SRR11621680, SRR11116102, SRR11960526, SRR11960527, SRR11960528, SRR11251333, SRR11960530, SRR11960617, SRR11960618, SRR11960622, SRR11960624, SRR11960625, SRR10959938, SRR11960628, SRR11960635, SRR11960631, SRR12643358, SRR10948215, SRR12071681, SRR11116103, SRR12071683, SRR10600524, SRR12174400, SRR12174404, SRR12174406, SRR12424844, SRR12424848, SRR12424849, SRR12424850, SRR12424853, SRR12424854, SRR12424855, SRR12424857, SRR12424858, SRR12424859, SRR12424861, SRR12584068, SRR12584069, SRR12584070, SRR12584071, SRR12584072, SRR12584073, SRR12584074, SRR12584075, SRR12584076, SRR12584077, SRR12584078, SRR12584079, SRR12584080, SRR12584081, SRR12584082, SRR12584083, SRR12584084, SRR12584085, SRR12584086, SRR12584089, SRR12586812, SRR12586813, SRR12586814, SRR12586815, SRR12586816, SRR12586819, SRR12586820, SRR12586821, SRR12586822, SRR12586823, SRR12586824, SRR12643343, SRR12643346, SRR12643347, SRR12643349, SRR12643353, SRR12643354, SRR12643356, SRR11187232, SRR11187240, SRR12643360, SRR12643361, SRR12643365, SRR12643367, SRR12643368, SRR12643371, SRR12663939, SRR12663940, SRR12663941, SRR12663942, SRR12663943, SRR12663944, SRR12706037, SRR12706039, SRR12706040, SRR12706041, SRR12706042, SRR12777348, SRR12777350, SRR12777351, SRR12824293, SRR11068078, SRR10546709, and SRR11230719.

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