Antimicrobial Resistance and CRISPR Typing Among Salmonella Isolates From Poultry Farms in China

Abstract

Although knowledge of the clustered regularly interspaced short palindromic repeat (CRISPR)-Cas system has been applied in many research areas, comprehensive studies of this system in Salmonella, particularly in analysis of antibiotic resistance, have not been reported. In this work, 75 Salmonella isolates obtained from broilers or broilers products were characterized to determine their antimicrobial susceptibilities, antibiotic resistance gene profiles, and CRISPR array diversities, and genotyping was explored. In total, 80.00% (60/75) of the strains were multidrug resistant, and the main pattern observed in the isolates was CN-AZM-AMP-AMC-CAZ-CIP-ATM-TE-SXT-FOS-C. The resistance genes of streptomycin (aadA), phenicol (floR-like and catB3-like), β-lactams (bla _TEM, bla _OXA, and bla _CTX), tetracycline [tet(A)-like], and sulfonamides (sul1 and sul2) appeared at higher frequencies among the corresponding resistant isolates. Subsequently, we analyzed the CRISPR arrays and found 517 unique spacer sequences and 31 unique direct repeat sequences. Based on the CRISPR spacer sequences, we developed a novel typing method, CRISPR locus three spacer sequences typing (CLTSST), to help identify sources of Salmonella outbreaks especially correlated with epidemiological data. Compared with multi-locus sequence typing (MLST), conventional CRISPR typing (CCT), and CRISPR locus spacer pair typing (CLSPT), discrimination using CLTSST was weaker than that using CCT but stronger than that using MLST and CLSPT. In addition, we also found that there were no close correlations between CRISPR loci and antibiotics but had close correlations between CRISPR loci and antibiotic resistance genes in Salmonella isolates.

Keywords: CRISPR array; CRISPR-Cas; Salmonella; antimicrobial resistance; molecular typing.

Figure 1

Resistance gene profiles from the Salmonella isolates.

Figure 2

Minimum spanning tree of Salmonella isolates from multi-locus sequence typing data.

Figure 3

Analysis of clustered regularly interspaced short palindromic repeat (CRISPR) leader and direct sequences (DRs). (A,B) Conservation analysis of leader sequences of CRISPR1 and CRISPR2, respectively. (C) Conservation analysis of DR sequences. Each logo is consisted of stacks of letters, one stack for each position in the sequence. The height of letters within each stack is measured in bits, with a maximum of two, and reflects the corresponding nucleotide conservation at that position. (D–F) Predicted secondary structure and MEF of a partial DR.

Figure 4

Spacer sequence profiles of CRISPR1 and CRISPR2 in Salmonella isolates. Each spacer is represented by a colored square and a geometric symbol based on the CRISPRviz. The gray square with × indicates deleted or missing spacer. The earliest acquired spacer is displayed on the left side and the newly acquired spacer is on the right side.

Figure 5

Unweighted pair group method with arithmetic mean (UPGMA) tree of Salmonella isolates. (A) UPGMA tree based on CRISPR locus spacer pair typing (CLSPT). (B) UPGMA tree based on CRISPR locus three spacer sequence typing (CLTSST). The same color indicates the same serotype.

Figure 6

Correlation heat map between CRISPR loci and antibiotics or antibiotic resistance genes in the total of 75 Salmonella isolates. (A) Correlation between CRISPR loci and antibiotics. (B) Correlation between CRISPR loci and antibiotic resistance genes. Correlation is expressed by Spearman correlation coefficient which is indicated by color gradient, red represents positive correlation, and blue represents negative correlation. ^** denotes p<0.01; ^* denotes p<0.05. Generally, a correlation coefficient above 0.7 indicates that the relationship is very close; 0.4–0.7 indicates that the relationship is close; and 0.2–0.4 indicates that the relationship is normal.