SU_BIO2071_W6_A2_BAKER_A

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Week 6 Project Ashley R Baker South University Microbiology Lab Professor: Pejmon Afshar Due: December 4, 2023 Week 6: Review Sheet Exercise 1: Disinfectant Bactericidal refers to a substance or a condition capable of killing bacteria. Bacteriostatic can inhibit the growth or reproduction of bacteria. Virucidal refers to having the capacity to or tending to destroy or inactivate viruses. Fungistatic can inhibit the growth and reproduction of fungi without destroying them (Morello, 2018). Control cultures are used to determine the effectiveness and sensitivity of a chemical agent as a disinfectant to the microorganisms present. It is important to know whether the disinfectant being used is viable or contaminated as well as whether it can kill, destroying or inactivating microbes or not (Morello, 2018). The factors that can influence the activity of a disinfectant include the number and location of microorganisms, innate resistance of microorganisms, concentration and potency of disinfectants, physical and chemical factors, organic and inorganic matter, duration of exposure, and biofilms. Reducing the number of microorganisms that must be inactivated through meticulous cleaning, increases the margin of safety when the germicide is used according to the labeling and shortens the exposure time required to kill the entire microbial load. The location of microorganisms also must be considered when factors affecting the efficacy of germicides are assessed. Only surfaces that directly contact the germicide will be disinfected, so there must be no air pockets and the equipment must be completely immersed for the entire exposure period (McDonnell & Russell, 1999).

Microorganisms vary greatly in their resistance to chemical germicides and sterilization processes. Intrinsic resistance mechanisms in microorganisms to disinfectants vary. Implicit in all disinfection strategies is the consideration that the most resistant microbial subpopulation controls the sterilization or disinfection time. That is, to destroy the most resistant types of microorganisms (bacterial spores), the user needs to employ exposure times and a concentration of germicide needed to achieve complete destruction. Except for prions, bacterial spores possess the highest innate resistance to chemical germicides, followed by coccidia (Cryptosporidium), mycobacteria (M. tuberculosis), nonlipid or small viruses (poliovirus, and coxsackievirus), fungi (Aspergillus, and Candida), vegetative bacteria (Staphylococcus, and Pseudomonas) and lipid or medium-size viruses (herpes, and HIV). Because these microorganisms contain lipids and are similar in structure and composition to other bacteria, they can be predicted to be inactivated by the same germicides that destroy lipid viruses and vegetative bacteria. A known exception to this supposition is Coxiella Brunetti , which has demonstrated resistance to disinfectants (McDonnell & Russell, 1999). With other variables constant, and with one exception (iodophors), the more concentrated the disinfectant, the greater its efficacy and the shorter the time necessary to achieve microbial kill. Generally not recognized, however, is that all disinfectants are not similarly affected by concentration adjustments. Considering the length of the disinfection time, which depends on the potency of the germicide, is also important. This was illustrated by Spaulding who demonstrated using the mucin-loop test that 70% isopropyl alcohol destroyed 10 M. tuberculosis in 5 minutes, whereas a simultaneous test with 3% phenolic required 2–3 hours to achieve the same level of microbial kill (McDonnell & Russell, 1999) . Several physical and chemical factors also influence disinfectant procedures: temperature, pH, relative humidity, and water hardness. An increase in pH improves the antimicrobial activity of some disinfectants (e.g., glutaraldehyde, quaternary ammonium compounds) but decreases the antimicrobial activity of others (phenols, hypochlorite’s, and iodine). The pH influences the antimicrobial activity by altering the disinfectant molecule or the cell surface. Relative humidity is the single most important factor influencing the activity of gaseous disinfectants/sterilant, such as EtO, chlorine dioxide, and formaldehyde. Water hardness (high concentration of divalent cations) reduces the rate of kill of certain disinfectants because

divalent cations (magnesium, calcium) in the hard water interact with the disinfectant to form insoluble precipitates (McDonnell & Russell 1999). Organic matter in the form of serum, blood, pus, or fecal or lubricant material can interfere with the antimicrobial activity of disinfectants in at least two ways. Most commonly, interference occurs by a chemical reaction between the germicide and the organic matter resulting in a complex that is less germicidal or nongermicidal, leaving less of the active germicide available for attacking microorganisms. The effects of inorganic contaminants on the sterilization process were studied during the 1950s and 1960s. This further emphasizes the importance of meticulous cleaning of medical devices before any sterilization or disinfection procedure because both organic and inorganic soils are easily removed by washing (McDonnell & Russell 1999). Items must be exposed to the germicide for the appropriate minimum contact time. The disinfectant must be introduced reliably into the internal channels of the device. The exact times for disinfecting medical items are somewhat elusive because of the effect of the aforementioned factors on disinfection efficacy. Certain contact times have proved reliable, but, in general, longer contact times are more effective than shorter contact times (McDonnell & Russell, 1999). Microorganisms may be protected from disinfectants by production of thick masses of cells and extracellular materials, or biofilms. Biofilms are microbial communities that are tightly attached to surfaces and cannot be easily removed. Once these masses form, microbes within them can be resistant to disinfectants by multiple mechanisms, including physical characteristics of older biofilms, genotypic variation of the bacteria, microbial production of neutralizing enzymes, and physiologic gradients within the biofilm (pH). Bacteria within biofilms are up to 1,000 times more resistant to antimicrobials than are the same bacteria in suspension (McDonnell & Russell, 1999). Microorganisms vary in their degree of susceptibility to disinfectants. In general, Gram- positive bacteria are more susceptible to chemical disinfectants while mycobacteria or bacterial endospores are more resistant. The hydrophilic, non-enveloped viruses (adenoviruses, picornaviruses, reoviruses, rotaviruses) are more resistant to disinfection than lipophilic, enveloped viruses (coronaviruses, herpesviruses, orthomyxoviruses, paramyxoviruses, retroviruses) (Russell A, 1999).

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Exercise 2: Antimicrobial Agent Susceptibility Testing and Resistance Antimicrobial resistance happens when germs like bacteria and fungi develop the ability to defeat the drugs designed to kill them. That means the germs are not killed and continue to grow. Resistant infections can be difficult, and sometimes impossible, to treat. Susceptibility is a term used when microbe such as bacteria and fungi are unable to grow in the presence of one or more antimicrobial drugs. Susceptibility testing is performed on bacteria or fungi causing an individual’s infection after they have been recovered in a culture of the specimen. Testing is used to determine the potential effectiveness of specific antibiotics on the bacteria and/or to determine if the bacteria have developed resistance to certain antibiotics (WHO, 2022). It is essential to use pure culture in antimicrobial susceptibility as it helps us ensure antimicrobial agents' effect on one bacterial species . If mixed culture is used, it becomes difficult to deduce the effect of antimicrobial agents on a specific microbial species since all would respond dissimilarly (Lagier, 2015). The three factors that can influence the accuracy of the test include sensitivity, specificity, predictive values, and likelihood ratios. It is the ability of a test or instrument to yield a positive result for a subject that has that disease. The ability to correctly classify a test is essential, and the equation for sensitivity is the following: Sensitivity= (True Positives (A))/ (True Positives (A)+False Negatives (C)) Sensitivity does not allow providers to understand individuals who tested positive but did not have the disease. False positives are considered through measurements of specificity and PPV. Specificity is the percentage of true negatives out of all subjects who do not have a disease or condition. In other words, it is the ability of the test or instrument to obtain normal range or negative results for a person who does not have a disease. The formula to determine specificity is the following: Specificity= (True Negatives (D))/(True Negatives (D)+False Positives (B))

Sensitivity and specificity are inversely related: as sensitivity increases, specificity tends to decrease, and vice versa. Highly sensitive tests will lead to positive findings for patients with a disease, whereas highly specific tests will show patients without a finding having no disease. Sensitivity and specificity should always merit consideration together to provide a holistic picture of a diagnostic test. Next, it is important to understand PPVs and NPVs. PPVs determine, out of all the positive findings, how many are true positives; NPVs determine, out of all the negative findings, how many are true negatives. Positive Predictive Value= (True Positives (A))/ (True Positives (A)+False Positives (B)) Negative Predictive Value= (True Negatives (D))/ (True Negatives (D)+False Negatives(C)) Disease prevalence in a population affects PPV and NPV. When a disease is highly prevalent, the test is better at ‘ruling in' the disease and worse at ‘ruling it out. Therefore, disease prevalence should also merit consideration when providers examine their diagnostic test metrics or interpret these values from other providers or researchers. Likelihood ratios (LRs) represent another statistical tool to understand diagnostic tests. LRs allow providers to determine how much the utilization of a particular test will alter the probability. A positive likelihood ratio, or LR+, is the probability that a positive test would be expected in a patient divided by the probability that a positive test would be expected in a patient without a disease. A negative likelihood ratio or LR-, is the probability of a patient testing negative who has a disease divided by the probability of a patient testing negative who does not have a disease. Unlike predictive values, and like sensitivity and specificity, likelihood ratios are not impacted by disease prevalence (NCBI, 2023). Broth dilution test is mainly used to check the sensitivity of a specific microorganism against an antibiotic. Growth control tube is a must as it helps to check bacterial growth . It is important to include a sterility control tube because it will help determine if the test was contaminated . The test is known to be contaminated if there is a growth of bacteria to determine the lowest concentration of the antimicrobial being investigated (Petersen & McLaughlin, 2021).

Reference: Morello, J. (2018). Lab Manual and Workbook in Microbiology: Applications to Patient Care (12th ed.). McGraw-Hill Higher Education (US). https://digitalbookshelf.southuniversity.edu/books/9781260163988 McDonnell, G., & Russell, A. D. (1999). Antiseptics and disinfectants: activity, action, and resistance. Clinical microbiology reviews , 12 (1), 147–179. https://doi.org/10.1128/CMR.12.1.147 Russell A. D. (1999). Bacterial resistance to disinfectants: present knowledge and future problems. The Journal of hospital infection , 43 Suppl , S57–S68. https://doi.org/10.1016/s0195- 6701(99)90066-x Antimicrobial Resistance Collaborators. (2022). Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. The Lancet; 399(10325): P629-655. DOI: https://doi.org/10.1016/S0140-6736(21)02724-0 Lagier, J. C., Edouard, S., Pagnier, I., Mediannikov, O., Drancourt, M., & Raoult, D. (2015). Current and past strategies for bacterial culture in clinical microbiology. Clinical microbiology reviews , 28 (1), 208–236. https://doi.org/10.1128/CMR.00110-14 Shreffler J, Huecker MR. Diagnostic Testing Accuracy: Sensitivity, Specificity, Predictive Values and Likelihood Ratios. [Updated 2023 Mar 6]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2023 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK557491/ Petersen, J., & McLaughlin, S. (2021, April 29). Examples of Bacterial Growth Characteristics in Broths, Slants and Plates. Queensborough Community College. https://bio.libretexts.org/@go/page/52228

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