Relationship of Biodiversity with Heavy Metal Tolerance and Sorption

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Relationship of biodiversity with heavy metal tolerance and sorption capacity: A meta-analysis approach Isis E Mejias Carpio, Ali Ansari, and Debora F. Rodrigues Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b04131 • Publication Date (Web): 27 Nov 2017 Downloaded from http://pubs.acs.org on November 29, 2017

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Environmental Science & Technology

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Relationship of biodiversity with heavy metal

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tolerance and sorption capacity: A meta-analysis

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approach

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Running title: Biodiversity and heavy metal Meta-analyses

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Isis E. Mejias Carpio a, Ali Ansari a, and Debora F. Rodrigues a,*

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Department of Civil and Environmental Engineering. University of Houston, Houston, TX-

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77004, USA

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E-mail: [email protected]

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*Corresponding Author: E-mail: [email protected]; Tel: 713-743-1495; Fax: 713-743-4260

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TOC/Abstract Art

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1 ACS Paragon Plus Environment


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Abstract

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Microbial remediation of metals can alleviate the concerns of metal pollution in the

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environment. The microbial remediation, however, can be a complex process since microbial

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metal resistance and biodiversity can play a direct role in the bioremediation process. This study

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aims to understand the relationships among microbial metal resistance, biodiversity, and metal

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sorption capacity. Meta-analyses based on 735 literature data points of Minimum Inhibitory

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Concentrations (MIC) of plantae, bacteria, and fungi exposed to As, Cd, Cr Cu, Ni, Pb, and Zn ─

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showed that metal resistance depends on the microbial Kingdom and the type of heavy metal,

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and that consortia are significantly more resistant to heavy metals than pure cultures. A similar

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meta-analysis comparing 517 MIC values from different bacterial genera (Bacillus, Cupriavidus,

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Klebsiella, Ochrobactrum, Paenibacillus, Pseudomonas, and Ralstonia) confirmed that metal

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tolerance depends on the type of genus. Another meta-analysis with 195 studies showed that the

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maximum sorption capacity is influenced by microbial Kingdoms, the type of Biosorbent

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(whether consortia or pure cultures), and the type of metal. This study also suggests that

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bioremediation using microbial consortia is a valid option to reduce environmental metal

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contaminations.

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Keywords: biosorption, heavy metals, microbial remediation, diversity, consortia

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1. Introduction

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In the past decade, multiple studies indicated that microorganisms can serve as potential

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alternatives for the sustainable remediation of heavy metals in the environment.1,

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investigations showed that microorganisms belonging to different Kingdoms, i.e. Fungi, Plantae,

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Eubacteria, are very promising for metal remediation.3 It is still unclear, however, whether the

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microorganisms from these Kingdoms have similar metal tolerance and sorption capacities.

These

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Most of the metal sorption studies in the literature use pure cultures, and only recently,

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researchers have been focusing on microbial communities.4, 5 The value of investigating pure

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cultures for heavy metal remediation is the discovery of the mechanisms of metal resistance and

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sorption capacity. Yet, pure culture studies are not practical for large-scale processes or realistic

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for in situ bioremediation, due to the difficulty in maintaining pure cultures and guaranteeing

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their optimum metal sorption capacity under different environmental conditions. Alternatively,

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microbial communities could be a more realistic approach for in situ remediation.

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The investigation of complex microbial communities for the sorption of heavy metals from

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the environment is promising, yet an unclear solution. Diverse microbial communities exist in

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the environment and may hold different sorption capacities or unknown mechanisms of metal

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resistance. But to date, very few studies have focused on understanding how microbial

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community diversity affects metal sorption.1, 6 In this context, we highlight the value of studying

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complex microbial communities to understand how biodiversity affects metal sorption processes

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in large-scale applications.

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In addition to research in biodiversity, studies in microbial metal tolerance up to date do not

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explain its effect on heavy metal sorption processes. The metal Minimum Inhibitory 3 ACS Paragon Plus Environment


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Concentration (MIC) of microbial cells is typically used as a first approach to determine the

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microbial metal resistance. MIC is commonly defined as the lowest metal concentration

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inhibiting microbial growth.7 Numerous studies have examined the heavy metal tolerance

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through the MIC of microorganisms isolated from different habitats, and grown under different

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conditions. But, to date, that large amount of data is still scattered, with no connection between

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metal resistance and microbial Kingdoms that could serve for a more effective bioremediation

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process.

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In this study, we collected 930 values from other literature studies that comprise common

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cells used for metal sorption and metal tolerance, with aims to: i) correlate microbial metal

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tolerance, in terms of MIC, the type of metal, the microbial Kingdom, and the bacterial genus ;

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ii) determine if the growth medium has an influence in the MIC; iii) link microbial metal

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sorption capacity with the types of metal and the microbial Kingdom; iv) associate the type of

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metal and the microbial Kingdom with the maximum sorption capacity (qmax); and v) determine

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if biodiversity has a significant effect on qmax by considering values of consortia and pure

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cultures. This approach will allow us to gain a better understanding of the role of microbial

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diversity, metal resistance, and metal sorption in bioremediation processes.

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2. Materials and Methods

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Parameters investigated

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The meta-analyses presented in this study were performed with data collected from the literature.

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Table 1 summarizes the categorical and dependent parameters applied. The subsequent sections

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describe the analyses performed with these parameters.

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Table 1- Number of literature results utilized for each analysis

Dependent Parameters Categorical Parameter

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Metal Tolerance, MIC

qmax

Microbial Kingdom (Eubacteria, Fungi, Plantae)

735

195

Types of Metal (As, Cd, Cr, Cu, Ni, Pb, Zn) Bacterial Genus (Bacillus, Cupriavidus, Klebsiella, Ochrobactrum, Paenibacillus, Pseudomonas, Ralstonia) Growth Medium (Minimum and Rich)

735

155

517

N/A

735

N/A

Biosorbent Type (Pure Cultures and Consortia)

735

155

N/A: data not available

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Analyses of Microbial Metal Tolerance relationships to Kingdoms, Bacterial Genus, Types of

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Metals, and Biosorbent type

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In this analysis, we collected 735 MIC results from the literature, as presented in Table 1.

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These MIC values belong to microorganisms from different Kingdoms under aerobic growth

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conditions. The data collected were analyzed using the ANOVA statistical analysis with Rstudio

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(see supporting information). In all analyses in this manuscript, the prokaryotic Kingdom of

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bacteria was treated as separate from Archaea, as stated by Woese and Fox.8

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The first analysis involved sorting the 735 MIC values into seven heavy metal groups (As,

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Cd, Cr, Cu, Ni, Pb, and Zn). The ‘type of metal’ was used as a categorical parameter and the

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MIC values included prokaryotes, eukaryotes, and consortia with both eukaryotic and

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prokaryotic microorganisms. A natural logarithm transformation of MIC values was done to

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obtain a normal distribution of the data. The ANOVA statistical analysis was done to determine

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if there was a statistically significant difference between the MIC values of all metal groups. In



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addition, the post hoc Tukey’s test was done to find out which metals had the highest and lowest

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values (see supporting information).

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In the second analysis, the ‘MIC’ value was used as a dependent parameter and the

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‘Kingdom’ (Eubacteria, Fungi, and Plantae) as a categorical parameter. Within those values, the

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analysis included pure cultures as well as consortia with either prokaryotes or eukaryotes, and

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consortia with both eukaryotic and prokaryotic microorganisms. The data included MIC values

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of the most common metals used in biosorption studies: As, Cd, Cr, Cu, Ni, Pb, and Zn. Most of

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the MIC studies used were short-term studies (maximum of 2 to 4 days of incubation). Some of

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the studies included tolerance assays done in one week and two were done in two weeks to a

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month. A natural logarithm transformation of MIC values was done to obtain a normal

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distribution of the data, presented in the supporting information. ANOVA statistical analysis was

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done to determine if there was a statistical difference among the three Kingdoms. In addition, the

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post hoc Tukey’s test was done to find out which group had the highest and lowest values (see

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supporting information).

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The third analysis involved evaluating 517 MIC values of pure cultures of different bacterial

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genera. This analysis aimed to determine whether specific genera could have different metal

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resistance. The most common genera of bacterium found to resist high concentrations of heavy

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metals are Acidithiobacillus sp., Desulfovibrio sp., E. coli sp., Cupriavidus sp., Ochrobactrum

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sp., Streptomyces sp., Micrococcus sp., Acinetobacter sp., and Pseudomonas sp.. However,

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because not enough data was available for all these genera, we utilized the most commonly

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studied microbes: Bacillus sp., Cupriavidus sp., Klebsiella sp., Ochrobactrum sp., Paenibacillus

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sp., Pseudomonas sp., and Ralstonia sp, as categorical parameters. A natural logarithm

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transformation of MIC values was done to obtain a normal distribution of the data. The ANOVA 6 ACS Paragon Plus Environment

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statistical analysis and post hoc Tukey’s test were done to determine which group had higher

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MIC values, as shown in the supporting information. For all analyses, the least square mean

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graphical representation was plotted with Rstudio.

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A fourth analysis involved 735 MIC values, but the MIC values were divided into two

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groups: minimum and rich media so that the ‘media’ represented a categorical parameter. The

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ANOVA statistical analysis and post hoc Tukey’s test were done to determine which group had

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higher MIC values.

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A fifth analysis involved the same 735 MIC values, but the MIC values were divided into

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two groups: pure cultures and consortia so that the ‘biosorbent type’ represented a categorical

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parameter. The ANOVA statistical analysis and post hoc Tukey’s test were done to determine

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which group had higher MIC values.

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Analysis of Microbial Maximum Sorption Capacity relationship to microbial kingdom and

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biosorbent type

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First, the relationship of the maximum sorption capacity, qmax, to the microbial kingdom was

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investigated with qmax values for various heavy metals from 195 published studies. The

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‘Kingdom’ (Eubacteria, Fungi, and Plantae) was used as a categorical parameter, whereas qmax

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was used as a dependent parameter.

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In a second analysis with 155 studies, the “metal” was used as a categorical parameter,

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whereas the qmax was used as a dependent parameter. The data included MIC values of common

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metals used in biosorption studies: Cd, Cr, Cu, Ni, Pb, and Zn only for the bacteria Kingdom.

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A third analysis included using “biosorbent type” (pure cultures or consortia) as a categorical

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parameter with the same 155 studies (97 for pure cultures and 58 for consortia from the bacteria 7 ACS Paragon Plus Environment


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Kingdom). These values were sorted into two main groups: Pure Cultures (PC) and Consortia

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(C). (Table 1).

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All consortia studies utilized in this analysis were a complex mixture of microorganisms

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obtained from environmental samples (e.g. soil, water or wastewater) grown in the laboratory

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with minimum media under aerobic conditions. None of the consortia studies were done in the

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study site.

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metals are present. The qmax values were calculated by the authors of each study. A few studies

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had only sorption capacity values, which were used from the highest reported observed values, or

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the maximum metal concentrations observed to be adsorbed, see Supporting Information. A

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natural logarithm transformation of qmax values was done to obtain a normal distribution of all

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of the data. The ANOVA statistical analysis and the post hoc Tukey’s test with Rstudio were

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done for the three analyses to determine which group had higher sorption capacity values, and

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the least square mean graphical representation was exported from Rstudio.

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Most of the qmax values were obtained from Langmuir isotherm data where excess

3. Results and Discussion

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3.1 Relationships among microbial kingdoms, bacterial genera, heavy metal tolerance, and

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bioremediation capability

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Microorganisms can differ in metal resistance and in their ability to remove heavy metals. In

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the scientific literature, diverse microorganisms from the Eubacteria, Fungi, and Plantae

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Kingdoms have shown evidence of heavy metal resistance. Within such Kingdoms, though,

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some metal-resistant microorganisms have never been investigated for heavy metal remediation

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capability.

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considering their remediation capability, to understand whether a particular Kingdom is more

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tolerant to heavy metals than others. Additionally, we also investigated the tolerance of different

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Thus, we first compared the MIC of different microbial Kingdoms, without


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Eubacterial genera to determine whether different genera can have different metal tolerances. We

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selected Eubacteria as a representative group for genus investigation since it is the most studied

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Kingdom in the literature. The next step of our evaluation was to compare the remediation

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capability of these Kingdoms in terms of metal sorption capacity. These results allowed us to

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determine (i) whether heavy metal tolerance is intrinsic to any particular microbial Kingdom; (ii)

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more specifically, whether the metal tolerance depends on the type of genus, and (iii) whether

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microorganisms from a particular Kingdom that are tolerant to metals can play a significant role

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in metal sorption capacity and hold bioremedation capabilities.

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Relationship between microbial metal tolerance and microbial Kingdom

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The relationship between microbial metal tolerance and Kingdom is key to determine the

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types of microorganisms that can survive in environments contaminated with heavy metals and

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potentially play a role in bioremediation processes. It is important, however, to first understand

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whether microbial metal tolerance is related to the type of metal since different metals have

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different redox capabilities, solubilities in water, and toxicity mechanisms under aerobic

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conditions. The analysis presented in Figure 1 shows that there is a statistically significant

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difference between the different metals and the overall microbial tolerance under the same redox

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conditions (aerobic), with a p-value 0.01),

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but are significantly different from As, Ni, Pb and Zn (Tukey’s test p0.01), but are



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significantly different from As and Pb (Tukey’s test p0.01), but are significantly different from

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the rest of the metals (Tukey’s test p Zn > Cd > Cu.68 The uptake of

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metals by yeast

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extracellular materials produced by yeasts.14

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3.2. Role of Biodiversity on Metal Tolerance and Sorption Capacity

has been attributed to intracellular sequestration and by the presence of

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All the studies analyzed in the previous sections included only pure cultures. Although pure

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cultures can have multiple metal resistance mechanisms, consortia can perform complicated

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functions that individual populations cannot.70 Consortia can also be more robust to

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environmental fluctuations, such as metal concentrations.70 Therefore, complex microbial

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communities are typically more attractive for large-scale processes and for in situ

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bioremediation.

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tolerance, and sorption capacity. For that purpose, we will compare results from studies with

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consortia, which contain multiple microbial species with various mechanisms of metal

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resistance, with results from studies with pure cultures. This approach will allow us to determine

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whether complex microbial communities are better at tolerating and removing heavy metals than

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pure cultures.

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Relationship between diversity and metal tolerance

In this study, we aim to establish relationships among biodiversity, metal



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The best way to determine whether microbial communities are more tolerant to metals than

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pure cultures is to perform an analysis comparing microbial metal resistance between consortia

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and pure cultures. Consortia in the present study represent communities of microorganisms

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found in heavy metal contaminated environments that were grown in the laboratory in synthetic

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minimum growth media prior to experimentation (e.g. MIC and sorption).

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The relationship between microbial metal resistance and biodiversity is critical to understand

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whether microbial diversity influences the mechanisms of metal tolerance. Figure 6 indicates

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that there is a statistically significant difference between the two groups, with a p < 0.001

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confidence level. The confidence level suggests that, on average, consortia have higher heavy

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metal resistance. The higher metal resistance of consortia may be explained by the effective

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communication between the microbial cells among different species. 91 Through communication

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between cells, microbial consortia can trigger changes in gene expression in response to high

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levels of metals. 71 The response to metal concentrations may happen by metabolic variations in

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several community members, shifting the concentration and fate of dissolved metabolites, to

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increase the tolerance for metals. 72

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Figure 6- Microbial metal resistance, expressed as the minimum inhibitory concentration, as a function of the biosorbent type. ANOVA results from 735 literature studies. Current effect: F(1,724)= 20.108, p

Relationship of Biodiversity with Heavy Metal Tolerance and Sorption

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