The Effects of Various Amino Acid Side Chains on B – Lactam Antibiotic Resistance

Antibiotic resistance has increased global deaths by 8% between 1990 and 2021 and is expected to be a leading cause of death by 2050 [1]. Based on projections, 11.1 million deaths due to Antimicrobial Resistance could be prevented if a treatment is devised to effectively inhibit Gram-negative B – Lactam bacteria that have undergone these mutations [1]. However, the lack of an effective antibiotic treatment is causing β– Lactam antibiotic resistance to be an unnecessary top cause of disease burden/death. This is why it is imperative to get down to the molecular mechanisms behind antibiotic resistance, so something can be done about this catastrophe. Now, I know I am just a Georgia Tech student. However, I hope to shed some light on this issue today, so I can communicate to the general public and to the non-scientists out there that this really is a solvable problem. It really is not as dire as it seems. So, sit back and relax, as I take you through a journey, looking into the history of β-Lactam Antibiotics, β-Lactam Antibiotic resistance, and mutations that have occurred that have allowed Gram-negative bacteria to become so powerful and what we as people can do about this!

β-Lactam Antibiotics, such as penicillin, have been used to treat a wide variety of bacterial infections due to the diversity of mechanisms with which they can work, such as their ability to promote the breakdown of the peptidoglycan layer of the cell wall via the targeting of binding proteins, transport proteins that transport peptidoglycan precursors across the cell wall, phospholipids that normally decrease permeability, etc [2]. Recently, however, the overreliance on β-Lactam Antibiotics has led to the development of resistance mechanisms in β-Lactam bacteria to counteract the effects of these antibiotics, the main one being the evolution of β-Lactamase enzymes [4]. This is due to evolutionary and selective pressure, which cause Gram-negative bacteria to develop resistance mechanisms to evade the effects of antibiotic treatment, especially though the development of mutations in their lactamase enzymes [4,5]. Resistance mechanisms in β-Lactam bacteria take the form of Standard beta-lactamase (SBL) and extended spectrum beta-lactamase (ESBL) mutations.

The two mutations differ primarily in their substrate specificity and the complexity of their mutations. SBL mutations enable SBLs to hydrolyze first-generation β-Lactam Antibiotics, whereas they fail to effectively enable hydrolysis of second or third-generation beta-lactamases [6, 7]. On the other hand, β-Lactam bacteria, with more complex mutations that help to increase the number of substrate– binding sites and the size of the active site, allow for the hydrolysis of a broader and more diverse range of antibiotics, increasing catalytic efficiency and conformational flexibility [7]. The result is more formidable antibiotic resistance, which poses a significantly greater threat compared to standard mutations [8]. Examples of β-Lactamase enzymes with these ESBL mutations are the TEM, KPC, and CTX-M enzymes. The danger with these mutations is that they spread easily through plasmids, which replicate independently of an organism’s chromosomal DNA and can transfer genes to other bacterial cells via horizontal gene transfer [9]. This means that mutations conferring resistance can quickly spread to multiple bacterial cells making it very difficult for antibiotic treatment to be successful [9,10]. Based on projections, 11.1 million deaths due to Antimicrobial Resistance could be prevented if a treatment is devised to effectively inhibit Gram-negative B – Lactam bacteria that have undergone these mutations [1]. This makes it imperative to better understand the molecular mechanisms behind what makes these Amino Acid mutations so advantageous in the TEM, KPC, and CTX-M enzymes so that more effective treatments to tackle antibiotic resistance can be devised. This paper focuses on the molecular mechanisms behind such mutations that enable Gram-negative bacteria to better bind to the side chains of extended-spectrum β-Lactam Antibiotics to help achieve that goal.

As alluded to earlier, mutations in Gram-negative bacterial proteins leading to resistance began with standard spectrum β-lactamase (SBL) mutations (S70 → S70G, E166 → E166N, K73 → K73H). The S70G mutation enabled β-lactamase enzymes to conduct a nucleophilic attack on the β-lactam ring, while the E166N and K73H mutations helped stabilize the transition state of this reaction with the side chains of β-lactam antibiotics, such as penicillin [11]. However, at this point, the worst-case scenario had not yet materialized because the active site of the β-lactamase enzymes could not accommodate extended-spectrum β-lactam antibiotics with bulky oxyimino side chains at the C7 position. These side chains were too large, and the active sites lacked the conformational flexibility to accommodate them [11]. The binding affinity (Km) was too high, and catalytic efficiency was too low for hydrolysis to occur. Extended-spectrum β-lactamase (ESBL) mutations, however, overcame this limitation by enhancing the ability of the bacteria to bind extended-spectrum β-lactam side chains. ESBL mutations, such as G238S, R164S, and E104K, expanded the active site through structural changes in the omega loop, allowing for new interactions between the enzyme and side chains, such as electrostatic interactions and hydrogen bonding [11, 12]. This significantly increased catalytic efficiency and decreased Km. Various gain-of-function mutations enabled β-lactamases to degrade β-lactam side chains more effectively, increasing the likelihood of significant antibiotic resistance [12].

For example, the G238S and R164S mutations in TEM enhance degradation by significantly increasing the conformational flexibility of the β-lactamase active site, by promoting the formation of Hydrogen bonding networks, allowing for the effective accommodation of the bulky R1 and R2 side chains of second-generation βlactam antibiotics, such as cefotaxime and ceftazidime [12]. This increased flexibility improves the binding affinity between the active site and the side chains, thereby increasing the acylation rate of cefotaxime and ceftazidime [12, 13]. As a result, catalytic efficiency and turnover rate also increase. Other mutations, such as E104K and E240K, further increase catalytic efficiency by enhancing electrostatic interactions between the β-lactamase active site and the β-lactam side chains, thus reducing aggregation and promoting proper folding [13, 14]. This phenomenon of enhanced hydrolysis due to increased flexibility is also seen in KPC β-lactamase, where the V240G and H274Y mutations improve the accommodation of the ceftazidime side chain by increasing the conformational flexibility of the β3 strand and introducing a tyrosine residue that participates in pi-stacking interactions with positively charged residues on the β-lactam side chain, further increasing catalytic turnover and facilitating hydrolysis [15].

Some mutations enhance the hydrolysis of β-lactam side chains by stabilizing the β-lactamase enzyme, enabling it to withstand other mutations that could otherwise destabilize it. For example, the M182T mutation introduces a polar side chain with a hydroxyl group, which can participate in hydrogen bond network formation [16]. This helps compensate for destabilizing effects caused by mutations such as G238S and E104K, by promoting correct protein folding and reducing the likelihood of significant aggregation [16]. Similarly, the A237T mutation introduces a polar side chain that facilitates hydrogen bonding and dipole–dipole interactions [16, 17]. In metalloβ-lactamases, such as New Delhi Metallo-β-Lactamase (NDM-1) and Verona-integron encoded metallo-βlactamase 2 (VIM-2), mutations like D124N, H189Y, H120R, and H263Y can enhance metal ion coordination within the active site, such as zinc binding, thus increasing overall enzyme stability and activity. These stabilizing mutations can offset the negative effects of destabilizing mutations, such as R244S, which weakens enzyme stability by disrupting ionic and hydrogen bond networks with the introduction of smaller polar side chains, and S130G in TEM-1 β-lactamase, which disrupts protein folding by affecting hydrophobic interactions in the core, breaking hydrogen bonding networks, and impairing the stabilization of enzyme loop regions due to the loss of a polar group after mutation [18, 19].

Finally, other mutations enhance the hydrolysis and degradation process by promoting the formation of new bonds, bond networks, and intermolecular forces between residues in the β-lactamase enzyme active site and the β-lactam side chains. Initially, wild-type CTX-M β-lactamase enzymes were ineffective at hydrolyzing the βlactam side chains of certain β-lactam antibiotics, such as ceftazidime, because the predominant mutations only allowed for the accommodation of smaller β-lactam side chains, such as those found on cefotaxime [11]. However, mutations that wild-type CTX-M β-lactamase enzymes later underwent, such as D240G and P167S, enhanced the fit of the aminothiazole ring of ceftazidime into the β-lactamase active site and altered the steric conformation of proline from cis to trans, respectively, allowing for the formation of electrostatic interactions and new hydrogen bonds with the β-lactam side chains [11, 20]. This occurs because Proline has an extremely rigid cyclic structure, so by mutating to Serine, its flexibility increases, enabling it to form more bonds. This ultimately increases catalytic efficiency and enhances hydrolysis [21].

Overall, these results suggest that key mutations, such as R164S & G238S in TEM, P167S & D240G in CTX-M, etc. work to induce resistance to β-lactam antibiotics, by promoting increased conformational flexibility, increasing the stabilization of the β-lactamase enzyme, and enabling the formation of new bonds between the active site residues on the enzyme, and the side chains of the antibiotics. The questions that remain are how these mutations can ultimately induce multi-drug resistance, either to different classes of antibiotics or different types of β-lactam bacteria, and what methods can be harnessed to specifically target β – Lactamase enzymes and slow down the rate at which they undergo mutations.

References

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  Timothy Durham was convicted of rape when a test showed his DNA genotype matched the DNA recovered from the crime scene. Eye witnesses testified that Durham was in a different state at the time of the incident, but he wasn’t exonerated from his 3000 year sentence until follow up DNA analysis showed that the preliminary forensic analysis used in the trial was misinterpreted (Thomas et al.). DNA testing serves an invaluable part in our criminal justice system, but it comes with complications and bias that can lead to wrongful convictions and misinformed juries.  

Background:

Forensic genetics aims to identify the origin of a biological sample. It can be traced back to Karl Landsteiner who discovered human ABO blood groups. With blood groups, suspects could be eliminated based on their blood type. For example, if a suspect had type A blood and there was type B blood left at the scene by the perpetrator, the investigators could rule out the suspect. Unfortunately, the reverse didn’t work. If the suspect and perpetrator both had the same blood type, it can’t be concluded that the suspect was guilty. Blood identifiers evolved into 8 distinct categories which improved the ability to eliminate suspects, but could only conclude that (if the system matched) it might be the perpetrator or this person might be related to the perpetrator (Jobling and Gill). The field evolved in the 1980s with the discovery of Minisatellites, lines of repetitive DNA that don’t encode proteins. Minisatellite patterns in DNA create what we know today as the DNA fingerprint, and it has a much higher accuracy rate than previous methods (Augustyn et al.). Around the same time, a breakthrough for victims of sexual assault was discovered. In the case of assault, bodily fluids of both the victim and the assaulter can get mixed. A process called differential lysis was created which could selectively increase the concentration of sperm in a fluid sample thereby allowing for accurate DNA testing (Jobling and Gill). Forensics evolved to use single-locus probe testing after several years because of its ease of interpretation. It looked at specific minisatellites that had high variability between subjects. This was the first DNA-based method to be used in a criminal investigation. Two murder homicides from several years apart were connected using DNA evidence. The evidence was then used to exonerate an innocent man, and the guilty party was found when he tried to evade mandatory DNA testing for all men in the small town. His guilt was then reinforced when the DNA profiles matched, and he gave a confession (Jobling and Gill). Finding DNA at a crime scene doesn’t guarantee that you’ll find a murderer. There are issues with non-pure samples and limited samples that make DNA work difficult, and accreditation of facilities and new techniques and take time (Jobling and Gill).  

Subjectivity of DNA Interpretation:

In a 2009 publication, the National Academy of Science discusses the possibility for subjective influence in lab based forensics. The interpretation bias happens in complex cases where, for example, there could be a mixture of DNA. A study published in 2011 looked specifically at this issue. A gang rape happened in Georgia, and the mixture in DNA from the case was used to prosecute one suspect after another suspect took a plea bargain to testify against him. With DNA mixtures, there are three possible conclusions: suspect excluded, suspect cannot be excluded, and inconclusive. If the suspect is excluded, it means that there’s little to no possibility that his DNA is part of the sample. If the suspect cannot be excluded, it means that there’s a possibility that his DNA is part of the sample. In the trial, the DNA examiners who knew the context of the case concluded that the suspect being prosecuted could not be excluded. The 2011 study gave the DNA evidence from this case and the DNA profiles of the suspects to 17 forensic examiners. These examiners had no context of the case, and they all worked independently. Of the 17, only 1 came to the same conclusion (suspect cannot be excluded) as the examiners who knew the context of the case. Twelve of the 17 concluded that the suspect who was prosecuted and convicted had no relation to the DNA found in the sample. Not only does this show that subjectivity occurs due to the context of the case, but the 17 examiners came up with different findings based on their past experiences meaning that not all DNA analysis is objective. Some organizations like the Scientific Working Group on DNA Analysis Methods say that quantitative statistical evidence should be presented with every categorical conclusion, but the US doesn’t require this (Dror and Hampikian).

False Positives:

There are two categories that cause wrongful identification in a DNA report: coincidental matches and false positives. Coincidental matches are DNA matches between two unrelated people. The probability of these matches is about 1 to 500,000 for white individuals and about 1 to 350,000 for black individuals. This small probability of coincidental matches makes people feel confident in DNA evidence. False positives, on the other hand, are matches between DNA and test DNA that result from issues in the forensics lab. There have been multiple cases of forensics labs accidentally switching victim and suspected rapist DNA which lead to convictions that were later overturned when the lab realized the error. There are also cases of misreading or misunderstanding a sample. In a case from 1993, a man was convicted of rape because someone interpreted a mixed sample of victim and perpetrator DNA as an individual sample. The conviction was again overturned. To prevent false convictions, retesting DNA is allowed, but it’s not an efficient solution. Many people are pushing for statistical information on the probability of false positives, so that the jurors can make accurate judgements based on DNA evidence (Thomas et al.).  

Conclusion:

DNA analysis is a useful tool for the criminal justice system, but subjectivity can be an issue in forensic testing. To combat wrongful convictions, there are organizations like The Innocence Project who use DNA testing to free the innocent, but reformed forensic testing standards should be put in place to prevent subjectivity and to ensure juries are correctly informed during trials. https://www.innocenceproject.org/    

Citation:

Augustyn , Adam, et al. “DNA Finerprinting.” Encyclopedia Britannica , 26 Apr. 2018, www.britannica.com/science/DNA-fingerprinting#ref153186. Dror, Itiel E., and Greg Hampikian. “Subjectivity and Bias in Forensic DNA Mixture Interpretation.” Science & Justice, vol. 51, no. 4, 2011, pp. 204–208., doi:10.1016/j.scijus.2011.08.004. Jobling, Mark A., and Peter Gill. “Encoded Evidence: DNA in Forensic Analysis.” Nature Reviews: Genetics, vol. 5, no. 10, Oct. 2004, pp. 739–751., doi:10.1038/nrg1455. Thompson, William C, et al. “How the Probability of a False Positive Affects the Value of DNA Evidence.” Journal of Forensic Sciences, vol. 48, no. 1, Jan. 2003, pp. 1–8., doi:10.1520/jfs2001171.