Antimicrobial resistance in human populations: challenges and opportunities

Allcock, Sophie H.; Eun, Young; Holmes, Mark A.; Gurdasani, Deepti; Dougan, Gordon; Sandhu, Manjinder S.; Solomon, Lee A.; Me, Török

doi:10.1017/gheg.2017.4

Cited by 105 publications

(79 citation statements)

References 45 publications

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“…When applied as a sole method, failures arise with increasing probing depths (≥5 mm) [4]. Systemic antibiotics improve the clinical outcomes, although their use should be restricted to severe cases [5], as antimicrobial use affects the gut microbiota [6] and is clearly associated with global development of antimicrobial resistance [7].…”

Section: Introductionmentioning

confidence: 99%

In Vitro Evaluation of Antimicrobial Activity of Minocycline Formulations for Topical Application in Periodontal Therapy

et al. 2020

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Periodontal therapy using antimicrobials that are topically applied requires slow or controlled release devices. The in vitro antimicrobial activity of biodegradable polymer formulations that contain a new minocycline lipid complex (P-MLC) was evaluated. The new P-MLC formulations that contained 11.5% minocycline were compared with pure minocycline or an existing commercial formulation, which included determination of minimal inhibitory concentration (MIC) values against two oral bacteria and activity on six-species periodontal biofilm. Moreover, the flow of gingival crevicular fluid (GCF) was modeled up to 42 days and the obtained eluates were tested both for MIC values and inhibiting biofilm formation. In general, MICs of the P-MLC formulations were slightly increased as compared with pure minocycline. Biofilm formation was clearly inhibited by all tested formulations containing minocycline with no clear difference between them. In 3.5 day old biofilms, all formulations with 250 µg/mL minocycline decreased bacterial counts by 3 log10 and metabolic activity with no difference to pure antimicrobials. Eluates of experimental formulations showed superiority in antimicrobial activity. Eluates of one experimental formulation (P503-MLC) still inhibited biofilm formation at 28 days, with a reduction by 1.87 log10 colony forming units (CFU) vs. the untreated control. The new experimental formulations can easily be instilled in periodontal pockets and represent alternatives in local antimicrobials, and thus warrant further testing.

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Section: Introductionmentioning

confidence: 99%

In Vitro Evaluation of Antimicrobial Activity of Minocycline Formulations for Topical Application in Periodontal Therapy

et al. 2020

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“…Sample preparation time could also be automated and optimized, for instance, the trypsin digestion here done in one hour might be reduced to a couple of minutes as reported in the literature (57,58). Finally, in a context where the emergence of resistant bacterial strains poses a global public health threat (59)(60)(61), the development of fast methods for bacterial typing becomes essential. Indeed, broad spectrum antimicrobials are commonly prescribed to patients before obtaining the results of the clinical microbiological analysis, a practice that might not be sufficient to control the infection, especially when one considers the risk posed by antibiotic-resistant species and their transmission in the hospital environment or the community (62).…”

Section: Discussionmentioning

confidence: 99%

Fast and accurate bacterial species identification in biological samples using LC-MS/MS mass spectrometry and machine learning

Roux‐Dalvai

Gotti

Leclercq

et al. 2019

Preprint

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The identification of microbial species in biological samples is essential to many applications in health, food safety and environment. MALDI-TOF MS technology has become a tool of choice for microbial identification but it has several drawbacks including: it requires a long step of bacterial culture prior to analysis (24h), it has a low specificity and is not quantitative. We have developed a new strategy for identifying bacterial species in biological samples using specific LC-MS/MS peptidic signatures. In the first training step, deep proteome coverage of bacteria of interest is obtained in Data Independent Acquisition (DIA) mode, followed by the use of machine learning to define the peptides the most susceptible to distinguish each bacterial species from the others. Then, in the second step, this peptidic signature is monitored in biological samples using targeted proteomics. This method, which allows the bacterial identification from clinical specimens in less than 4h, has been applied to fifteen species representing 84% of all Urinary Tract Infections (UTI). More than 31000 peptides in 200 samples have been quantified by DIA and analyzed by machine learning to determine an 82 peptides signature and build prediction models able to classify the fifteen bacterial species. This peptidic signature was validated for its use in routine conditions using Parallel Reaction Monitoring on a capillary flow chromatography coupled to a Thermo Scientific™ Q Exactive HF-X instrument. Linearity and reproducibility of the method were demonstrated as well as its accuracy on donor specimens. Within 4h and without bacterial culture, our method was able to predict the predominant bacteria infecting a sample in 97% of cases and 100% above the 1×105 CFU/mL threshold commonly used by clinical laboratories. This work demonstrates the efficiency of our method for the rapid and specific identification of the bacterial species causing UTI and could be extended in the future to other biological specimens and to bacteria having specific virulence or resistance factors.

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“…It is alarming that common bacterial infections are becoming difficult to treat due to antibiotic resistant bacteria. The problem often more focuses in human health sector and poultry industry (Hassan et al, 2014;Allcock et al, 2017), but information on small ruminant, particularly on goat population has not been well studied. Several mechanisms of resistance have been evolved by the bacteria to continue infection, despite use of an antibiotic.…”

Section: Introductionmentioning

confidence: 99%

A Cross Sectional Anthropo-Clinical Study on Antimicrobials Prescription Pattern in Goat Patients at Chittagong, Bangladesh

Bhowmik¹,

Ahaduzzaman²,

Hasan³

2018

Bangl. J. Vet. Med.

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In the last three decades use of antibiotics in livestock sector has grown tremendously. The uses of these antibiotics have profound impacts on animal health, farmer income and public health. From April, 2016 to March, 2017, a hospital based retrospective study was conducted using clinical record sheet of goat patients (N=1405) at Teaching Veterinary Hospital (TVH) of Chittagong Veterinary and Animal Sciences University (CVASU), Bangladesh; to assess the groups of antimicrobials used, perception of goat owners' on antibiotics and the annual therapeutic costs for antibiotics that had been used for the treatment of goats at TVH. At TVH, the most prescribed antibiotic was streptomycin-penicillin [437 (31.10%)], whereas the least used antibiotic was tylosin [7 (0.49 %)]. From anthopo-clinical analysis, only 24% farmers said they are familiar with the term "antibiotic", but no farmer had any ideas about antimicrobial resistance and its withdrawal period. Considering the average body weight 20-30 kg of goat patients' we calculated the cost of antibiotic purchase and found the highest money (968.18-1450.04 U.S. Dollars/annum) was expenditure to purchase Gentasone plus ® (gentamicine-sulfadiazinetrimithoprime) and the lowest (5.37-8.06 USD/annum) was for tylosin. Ensuring and dissemination of proper knowledge to the farmer regarding antibiotics will prevent them from self purchase and irrational use therefore will help us to reduce the risk of antibiotic resistance in food animal.

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Antimicrobial resistance in human populations: challenges and opportunities

Cited by 105 publications

References 45 publications

In Vitro Evaluation of Antimicrobial Activity of Minocycline Formulations for Topical Application in Periodontal Therapy

In Vitro Evaluation of Antimicrobial Activity of Minocycline Formulations for Topical Application in Periodontal Therapy

Fast and accurate bacterial species identification in biological samples using LC-MS/MS mass spectrometry and machine learning

A Cross Sectional Anthropo-Clinical Study on Antimicrobials Prescription Pattern in Goat Patients at Chittagong, Bangladesh

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