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. 2024 Feb 13;9(8):8862-8873.
doi: 10.1021/acsomega.3c05902. eCollection 2024 Feb 27.

Optical Mapping: Detecting Genomic Resistance Cassettes in MRSA

Elizabete Ruppeka-Rupeika  1 , Sergey Abakumov  1 , Mattias Engelbrecht  2 , Xiong Chen  1 , Debora do Carmo Linhares  1 , Arno Bouwens  2 , Volker Leen  2 , Johan Hofkens  1   3
Affiliations

Optical Mapping: Detecting Genomic Resistance Cassettes in MRSA

Elizabete Ruppeka-Rupeika et al. ACS Omega. .

Abstract

Methicillin-resistant Staphylococcus aureus (MRSA) is a multidrug-resistant bacterium with a global presence in healthcare facilities as well as community settings. The resistance of MRSA to beta-lactam antibiotics can be attributed to a mobile genetic element called the staphylococcal cassette chromosome mec (SCCmec), ranging from 23 to 68 kilobase pairs in length. The mec gene complex contained in SCCmec allows MRSA to survive in the presence of penicillin and other beta-lactam antibiotics. We demonstrate that optical mapping (OM) is able to identify the bacterium as S. aureus, followed by an investigation of the presence of kilobase pair range SCCmec elements by examining the associated OM-generated barcode patterns. By employing OM as an alternative to traditional DNA sequencing, we showcase its potential for the detection of complex genetic elements such as SCCmec in MRSA. This approach holds promise for enhancing our understanding of antibiotic resistance mechanisms and facilitating the development of targeted interventions against MRSA infections.

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Conflict of interest statement

The authors declare the following competing financial interest(s): Arno Bouwens and Mattias Engelbrecht are employees of Perseus Biomics. Johan Hofkens and Volker Leen are co-founders of Perseus Biomics.

Figures

Figure 1
Figure 1
Fluorocode workflow. Above, from left: bacteria carrying different SCCmec cassettes. First, high molecular weight (HMW) DNA extraction is performed. Then, a one-pot labeling reaction follows, where the M.Taq methyltransferase delivers a fluorophore to its specific recognition site. The labeling reaction results in covalently bound labels at the M.Taq recognition sites on the double-stranded DNA molecule. Below, from left: labeled DNA is deposited using the rolling droplet technique, and the linearized DNA is tile-scanned using a widefield fluorescence microscope. Subsequently, the tile-scans are segmented to select the DNA traces, which are recorded as a signal barcode. An intensity trace is generated from the barcode and is cross-correlated against an in silico-generated candidate intensity trace from a database entry.
Figure 2
Figure 2
(A) The associated SCCmec type is indicated next to the name of the strain. The legend on the right indicates color representation of SCCmec in the graph. The three panels illustrate (in order from left) the simulations in Widefield and SIM systems, following the results from wet lab experiments with ATCC samples imaged with a WF system. The stacked bar charts document the abundance of the SCCmec type detected. The SCCmec was detected in all the cases except 11819-97, where we hypothesize that the SCCmec is truncated to a size below the limit of detection by Fluorocode OM. To test this hypothesis, we simulated the MSSA strain ATCC 12600 to contain the SCCmec Type IV cut up into three pieces (6, 8, and 12 kbp) randomly inserted into the genome. As expected, in this case, no SCCmec was detected neither with WF nor SIM, contributing to a positive conclusion for the truncation hypothesis, as these results coincide with the results of the strain 11819-97. The simulations with SR-SIM microscopy show that most false-positive matches are eliminated, while with WF alone, there are about 12.5% of false positives for NCTC 10442 and T0131. While eliminating FPs is preferable, the loss of time using SR-SIM outweighed the gain in TP abundance, as at >85% abundance of a single SCCmec, we consider the match of good quality. The WF results show that experimentally, Fuorocode OM detects the absence and presence of SCCmec correctly in both cases for ATCC 12600 and ATCC 43300, respectively. No FPs were observed. (B) The experimental data sets were tested for ground truth detection as a control. The strain ATCC 12600 was matched to itself at a little less than 75% and exhibits an average nucleotide identity (ANI) of 99.83% with NCTC 8325, the second most abundant matching species at about 25%. The status of this match as an FP is not obvious, given the sequence similarity between the two strains. The third strain showing up with about 5% matches is the S. aureus genome that is provided by the commercial bacterial mixture used for the other experiment. In the meantime, the strain ATCC 43300 has an ANI of 97.45% with NCTC 8325 and 97.55% with ATCC 12600, which turned out to be sufficiently different to tell the strains apart with the Fluorocode OM workflow presenting ∼1% of FPs each.
Figure 3
Figure 3
(A) Three samples of seven bacterial genomic DNA in equal proportions spiked with 0.01, 0.1, and 10% MRSA (ATCC 43300) DNA, respectively. All three samples show detection of the MRSA strain separately from S. aureus originally present in the mixture. (B) “zoom in” of the stacked bar. The exact percentage of the ATCC 43300 detection is 0.42, 0.94, and 14.48% for the 0.01, 0.1, and 10% spike-ins, respectively.
Figure 4
Figure 4
Readout summary from the SCCmecFinder pipeline. All the strains investigated in this work are presented on the y axis, with MRSA or MSSA status indicated in the brackets. The k-mer template coverage in percentage is one of the metrics of SmF for determining a SCCmec-type presence. The lowest reliable threshold for template coverage proposed by the Larsen group is 50%, and all the MRSA strains investigated in this work exhibit well above 75% of k-mer template coverage.
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