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Frontiers of Environmental Science & Engineering

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Front. Environ. Sci. Eng.    2019, Vol. 13 Issue (3) : 44    https://doi.org/10.1007/s11783-019-1128-1
RESEARCH ARTICLE
Detection of presumed genes encoding beta-lactamases by sequence based screening of metagenomes derived from Antarctic microbial mats
Gastón Azziz1,2(), Matías Giménez1, Héctor Romero3, Patricia M. Valdespino-Castillo4, Luisa I. Falcón5,6, Lucas A. M. Ruberto7,8, Walter P. Mac Cormack7,8, Silvia Batista1
1. 1Molecular Microbiology Unit, Clemente Estable Biological Research Insitute, UdelaR, Montevideo 11600, Uruguay
2. Microbiology Laboratory, Faculty of Agronomy, UdelaR, Montevideo 12900, Uruguay
3. Genome Organization and Evolution Laboratory, Ecology and Evolution Department, Faculty of Sciences, UdelaR, Montevideo 11400, Uruguay
4. Molecular Biophysics and Integrated Bioimaging, BSISB Imaging Program, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
5. Bacteial Ecology Laboratory, Ecology Institute, National Autonomous University of Mexico, CDMX 04510, Mexico
6. UNAM, Yucatan Technology and Science Park, Merida 97302, Mexico
7. Argentine Antarctic Institute, Buenos Aires 1650, Argentina
8. Biotechnology Unit, Faculty of Pharmacy and Biochemistry, Nanobiotec Institute UBA-CONICET, Buenos Aires 1113, Argentina
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Abstract

• Beta-lactamase genes were found in all samples from distant places in Antarctica.

• Class C beta-lactamase coding genes were the most frequently found.

• Diversity of sequences exceeds that of the beta-lactamases from clinical environment.

Analysis of environmental samples for bacterial antibiotic resistance genes may have different objectives and analysis strategies. In some cases, the purpose was to study diversity and evolution of genes that could be grouped within a mechanism of antibiotic resistance. Different protocols have been designed for detection and confirmation that a functional gene was found. In this study, we present a sequence-based screening of candidate genes encoding beta-lactamases in 14 metagenomes of Antarctic microbial mats. The samples were obtained from different sites, representing diverse biogeographic regions of maritime and continental Antarctica. A protocol was designed based on generation of Hidden Markov Models from the four beta-lactamase classes by Ambler classification, using sequences from the Comprehensive Antibiotic Resistance Database (CARD). The models were used as queries for metagenome analysis and recovered contigs were subsequently annotated using RAST. According to our analysis, 14 metagenomes analyzed contain A, B and C beta-lactamase genes. Class D genes, however, were identified in 11 metagenomes. The most abundant was class C (46.8%), followed by classes B (35.5%), A (14.2%) and D (3.5%). A considerable number of sequences formed clusters which included, in some cases, contigs from different metagenomes. These assemblies are clearly separated from reference clusters, previously identified using CARD beta-lactamase sequences. While bacterial antibiotic resistance is a major challenge of public health worldwide, our results suggest that environmental diversity of beta-lactamase genes is higher than that currently reported, although this should be complemented with gene function analysis.
Keywords Beta-lactamases      Antibiotic resistance coding genes      Metagenomes      Antarctic microbial mats     
Corresponding Author(s): Gastón Azziz   
Issue Date: 26 June 2019
 Cite this article:   
Gastón Azziz,Matías Giménez,Héctor Romero, et al. Detection of presumed genes encoding beta-lactamases by sequence based screening of metagenomes derived from Antarctic microbial mats[J]. Front. Environ. Sci. Eng., 2019, 13(3): 44.
 URL:  
https://academic.hep.com.cn/fese/EN/10.1007/s11783-019-1128-1
https://academic.hep.com.cn/fese/EN/Y2019/V13/I3/44
Sample Geographic reference Latitude Longitude
Sample 1 King George Island (Fildes Peninsula) 62°09′31” S 58°56′31’ W
Sample 2 King George Island (Fildes Peninsula) 62°09′59” S 58°58′33” W
Sample 3 King George Island (Fildes Peninsula) 62°12′14” S 58°57′16” W
Sample 4 King George Island (Fildes Peninsula) 62°10′0” S 58°58′34” W
Sample 5 King George Island (Potter Peninsula) 62°14′35” S 58°40′39” W
Sample 6 King George Island (Potter Peninsula) 62°14′34” S 58°40′26” W
Sample 7 Antarctic Peninsula (Trinity Peninsula) 63°28′13” S 57°12′3” W
Sample 8 Antarctic Peninsula (Danco Coast) 64°09′22” S 60°57′30” W
Sample 9 Antarctic Peninsula (Fallieres Coast) 68°07′45” S 67°06′2” W
Sample 10 McMurdo Dry Valleys 78°01′24” S 163°55′03” E
Sample 11 McMurdo Dry Valleys 78°01′23” S 163°54′56” E
Sample 12 McMurdo Dry Valleys 78°01′23” S 163°54′07” E
Sample 13 McMurdo Dry Valleys 78°01′30” S 164°06′02” E
Sample 14 McMurdo Dry Valleys 77°39′40” S 163°05′31” E
Tab.1  Geographic location of sampling sites
Class A Class B
Samplea) Primary Hits (n) Confirmed Hits (n) Confirmed
Hits (‰)		 Primary Hits (n) Confirmed Hits (n) Confirmed
Hits (‰)
Metagenome 1 (14344) 4 2 0.139 17 6 0.418
Metagenome 2 (3760) 10 3 0.798 33 5 1.330
Metagenome 3 (3724) 8 1 0.269 14 6 1.611
Metagenome 4 (4706) 7 4 0.850 28 8 1.700
Metagenome 5 (15035) 42 13 0.865 78 21 1.397
Metagenome 6 (11962) 32 8 0.669 66 15 1.254
Metagenome 7 (9291) 21 8 0.861 67 16 1.722
Metagenome 8 (10127) 39 12 1.185 72 19 1.876
Metagenome 9 (7315) 14 5 0.684 64 34 4.648
Metagenome 10 (6973) 20 7 1.004 53 15 2.151
Metagenome 11 (9269) 22 13 1.403 68 24 2.589
Metagenome 12 (8972) 7 2 0.223 76 15 1.672
Metagenome 13 (7187) 13 5 0.696 58 16 2.226
Metagenome 14 (11580) 21 10 0.864 71 32 2.763
Tab.2  Number and per mille of beta-lactamase hits found for classes A and B in each metagenome
Class C Class D
Samplea) Primary Hits (n) Confirmed Hits (n) Confirmed
Hits (‰)		 Primary Hits (n) Confirmed Hits (n) Confirmed
Hits (‰)
Metagenome 1 (14344) 19 12 0.837 0 0 0
Metagenome 2 (3760) 27 10 2.660 9 2 0.532
Metagenome 3 (3724) 17 7 1.880 4 1 0.269
Metagenome 4 (4706) 21 10 2.125 8 0 0
Metagenome 5 (15035) 58 19 1.264 22 1 0.067
Metagenome 6 (11962) 75 26 2.174 28 1 0.084
Metagenome 7 (9291) 36 14 1.507 21 2 0.215
Metagenome 8 (10127) 70 26 2.567 26 5 0.494
Metagenome 9 (7315) 86 44 6.015 10 3 0.410
Metagenome 10 (6973) 51 23 3.298 14 2 0.287
Metagenome 11 (9269) 64 32 3.452 14 3 0.324
Metagenome 12 (8972) 62 19 2.118 9 2 0.223
Metagenome 13 (7187) 43 25 3.479 8 1 0.139
Metagenome 14 (11580) 79 39 3.368 15 0 0
Tab.3  Number and per mille of beta-lactamase hits found for classes C and D in each metagenome
Fig.1  Phylogenetic tree constructed with deduced amino acid sequences of class A beta-lactamases identified in Antarctic microbial mat metagenomes. Representative reference sequences were also included in the tree. The tree was constructed using Neighbor Joining algorithm.
Fig.2  Phylogenetic tree constructed with deduced amino acid sequences of class B beta-lactamases identified in Antarctic microbial mat metagenomes. Representative reference sequences were also included in the tree. The tree was constructed using Neighbor Joining algorithm.
Fig.3  Phylogenetic tree constructed with deduced amino acid sequences of class C beta-lactamases identified in Antarctic microbial mat metagenomes. Representative reference sequences were also included in the tree. The tree was constructed using Neighbor Joining algorithm.
Fig.4  Phylogenetic tree constructed with deduced amino acid sequences of class D beta-lactamases identified in Antarctic microbial mat metagenomes. Representative reference sequences were also included in the tree. The tree was constructed using Neighbor Joining algorithm.
Class Shannon index of metagenome sequences Shannon index of database sequences
Class Aa) 2.94 (n = 93) 1.35 (n = 660)
Class Ba) 3.32 (n = 232) 2.30 (n = 163)
Class Ca) 4.85 (n = 306) 0.72 (n = 226)
Class Da) 1.54 (n = 23) 1.66 (n = 292)
Tab.4  Shannon diversity indexes for each class of beta-lactamases for sequences retrieved from the Antarctic metagenomes and from CARD database
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